A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> This paper proposes a technique of iterative dynamic programming to plan minimum energy consumption trajectories for robotic manipulators. The dynamic programming method is modified to perform a series of dynamic programming passes over a small reconfigurable grid covering only a portion of the solution space at any one pass. Although strictly no longer a global optimization process, this iterative approach retains the ability to avoid some poor local minima while avoiding the curse of dimensionality associated with a pure dynamic programming approach. The algorithm has an inherent parallel structure, allowing for reduced computation time on parallel architecture computers. No limiting assumptions are made about the performance index, or function to be optimized. As such, extremely complex functions and constraints are easily handled. Joint actuator and time constraints are considered in this work. The modified dynamic programming approach is verified experimentally by planning and executing a minimum energy consumption path for a Reis V15 industrial manipulator. <s> BIB001 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> The motion profile for point-to-point control under acceleration, which is applied to many applications in electro-mechanical systems, should be planned so as to maximize the energy conversion efficiency. Initially, a theoretically ideal profile was derived by adopting Pontryagin's minimum principle. The performance of this energy efficient motion profile is compared to those of three conventional profiles widely used in practice: trapezoidal, variable-rate transymmetric, and exponential. Finally, a selection guide for motion profile is presented for applications in which energy conversion efficiency and peak acceleration become critical, such as the material handling machine, copying machine, various dedicated purpose machines, electric motor cars, and space vehicles. <s> BIB002 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> In this paper a method to solve the trajectory generation problem in redundant degree of freedom manipulator has been proposed, and the variational approach within the B-spline function are introduced for minimization of the consumed electrical energy of a robot manipulator system. In the proposed method, the inverse matrix of Jacobian calculation is not required, and the minimal trajectory error is guaranteed while minimizing the consumed electrical energy. The theory, simulation, and experiments are presented in the paper. <s> BIB003 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> This paper considers the control problem of a robotic manipulator with separately excited dc motor drives as actuators. An innovative method is proposed which achieves robot speed-control requirements, with simultaneous minimization of total electromechanical losses, while the drives follow the desired speed profiles of the robot joints under various loads and random load disturbances. If there is no demand for a specific speed profile, the optimal speed trajectory is determined by minimizing an electromechanical losses criterion. Controllable energy losses, such as armature copper losses, armature iron losses, field copper losses, stray load losses, brush load losses, friction and windage losses, can be expressed proportionally to the squares of the armature and the field (exciting) currents, the angular velocity and the magnetic field flux. The controllable energy loss term is also included in the optimal control integral quadratic performance index, defined for the whole operation period. Thus the appropriate control signals required for following the desired trajectory by simultaneous energy loss minimization for the whole operation interval are achieved. Two case studies of optimal robot control with and without minimization of actuator energy losses are presented and compared, showing the energy savings that can be achieved by the proposed methodology. <s> BIB004 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> An optimized path-planning approach is presented for flexible dynamic systems. Feedforward command profiles are determined for rest-to-rest large angle maneuvers that keep vibrations to a minimum. The performance index included both minimum energy and minimum time optimization problems. The feedfoward command profiles were generated by solving a discrete-time optimal control problem via discrete dynamic programming (DDP). A simple planar two-link flexible robot arm was utilized to demonstrate the DDP path-planning scheme. Numerical simulation results included: 1) minimum effort, 2) minimum effort with bounds, 3) minimum time, and 4) minimum torque-rate or power, respectively. The DDP approach demonstrated an effective alternative for numerical optimization, to generate optimal feedforward trajectory profiles. <s> BIB005 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> In this paper, the optimal time-energy trajectory planning problem for a three degrees-of-freedom planar manipulator is considered using a multi-level fuzzy-neural system. First, a neural network is achieved to solve the inverse kinematics problem (IKP). After pre-processing steps characterizing the minimum time trajectory and the corresponding torques, a fuzzy-neuro controller is developed to deal with the minimum energy trajectory planning. The basic function of this controller is to select the minimum energy link actuator torques allowing the robot end-effector to move from a starting point S to a target point T. This optimization is performed under actuators and workspace constraints. It starts with a fuzzy clustering of input-output data, uses Tsukamoto fuzzy inference and back-propagation algorithm to train the resulting adaptive neural network. The premises parameters (antecedent membership functions parameters) as well as rule-consequence parameters are then learned and optimized, giving the optimal energy torques. Simulation results are provided to prove the efficiency of the proposal. <s> BIB006 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> Optimal trajectory planning for robot manipulators is a very important issue in the research field of robotics. Many applications require smooth trajectories and the minimization of a performance index, usually the traveling time or the mechanical energy of the actuators. This paper presents a novel method that uses eighth-degree polynomial functions to generate smooth trajectories for the parametric representation of a given path. The optimization algorithm presented in this paper minimizes the mechanical energy consumed in the robot manipulator. To solve the optimization model, a genetic algorithm is implemented. A software platform has been developed to test this optimal trajectory-planning algorithm. The software includes modules to solve the direct kinematics, the inverse kinematics, and the dynamics of the robot manipulator. <s> BIB007 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> A new method of minimum-energy point-to-point (PTP) trajectory planning is proposed for an LCD glass-handing robot, which is driven by a permanent magnet synchronous motor (PMSM). The variable structure controller (VSC) is designed to track the trajectories and compensate LuGre model of frictional torque effects. The robot system is described by a mechanical equation and an electrical equation. To generate the minimum-energy trajectory, we employ a high-degree polynomial with suitable end-point conditions. The real-coded genetic algorithm (RGA) is used to search for the coefficients of the polynomial with the fitness function of minimum-energy input. Finally, numerical simulations of the minimum-energy inputs are compared for various degrees of polynomials. It is concluded that the proposed methodology can effectively design the minimum-energy trajectory, and the nonlinear VSC can track the designed trajectories for the robot system driven by a PMSM. <s> BIB008 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> The main objective of this paper is to propose a novel minimum-energy trajectory planning for an LCD glass-handing robot, which is driven by a permanent magnet synchronous motor (PMSM). The system is described by a mathematical model of the electromechanical system. To generate the minimum-energy trajectory, we employ a high-degree polynomial with suitable conditions of angular displacement, speed, acceleration and jerk at the start and end points. The real-coded genetic algorithm (RGA) is used to search for the minimum-energy point-to-point (PTP) trajectory for the motion profile. The coefficients of the polynomial are determined by the RGA with the fitness function of minimum-energy input. The results are compared for various degrees of polynomials and to obtain the minimum energy input. It is concluded that the proposed methodology with minimum-energy input can also be applied to any electromechanical system driven by a PMSM. <s> BIB009 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> In this paper, we propose a novel trajectory planning method for a precision positioning table driven by a permanent magnet synchronous motor (PMSM). To generate the mechatronic trajectory we develop a real-coded genetic algorithm (RGA) to search for the optimal trajectory for the motion. In this method, we design a high-degree polynomial to compute minimum-energy trajectories, and consider the problem of initial and final constraints in the algorithm. The RGA determines the parameters, which are to formulate the polynomial, and satisfy the desired fitness function of the minimum input energy. The adaptive control (AC) are developed based on mathematical knowledge of the precision positioning table and the PMSM. The proposed adaptive control is robust not only to parametric uncertainties of mass variations but also to external disturbances. The effectiveness of the proposed trajectory planning and adaptive control are demonstrated by numerical simulations in the point to point motion processes for the precision positioning table. <s> BIB010 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> In this paper, we propose a novel minimum-energy point-to-point (PTP) trajectory planning method for a simple mechatronic system, which is a one-dimensional precision positioning table driven by a permanent magnet synchronous motor (PMSM). To generate the mechatronic trajectory we develop a real-coded genetic algorithm (RGA) to search for the optimal trajectory for the PTP motion. In this method, we design a high-degree polynomial to compute minimum-energy point-to-point trajectories, and consider the problem of initial and final constraints (position, velocity, acceleration and jerk) in the algorithm. The RGA determines the parameters, which are to formulate the polynomial, and satisfy the desired fitness function of the minimum input energy. The algorithm is tested in numerical simulations results and yields good results for the comparisons between the seven-degree to twelve-degree polynomial during motion operations. <s> BIB011 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> A method for the regenerative energy saving in multi-axis servo-motor-drives is presented in this paper. This energy management is achieved through a proper time-coordination between the speed commands of multi-axis drives. Moreover, the proposed approach significantly limits the peak value of the ac input current in these systems. It is mathematically proved that a time-delay can significantly increase the amount of utilized regenerative energy and consequently decreases the amount of dissipated energy. In this paper, a set of closed-form formulas is developed, where the motor losses are neglected. The findings of this investigation were experimentally verified using a two-axis permanent-magnet (PM) motor-drive system, and the results are presented in this paper. The experimental results are in remarkable agreement with the developed closed-form formulas. <s> BIB012 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> In this paper we propose an energy efficient method for path planning by a robot arm. First we have developed a cost function that provides a set of via points determining a suitable path according to the obstacles present in the surroundings and other restrictions in its motion. Then we fit a suitable polynomial to this set of interior points to ensure that the journey is smooth and takes place with the consumption of minimum energy. The set of via-points as well as the minimum energy path have been determined using IWO (Invasive Weed Optimization) which is a new search heuristic based on the colonizing property of weeds. Application of such evolutionary algorithms in trajectory planning is advantageous because the exact solution to the path planning problem is not always available beforehand and must be determined dynamically. The entire procedure has been demonstrated through simulations. The above formulation is very simple and versatile and can be effectively applied to a variety of situations. <s> BIB013 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> This paper quantitatively reports about potential energy savings on robotic assembly lines for the automotive industry. The key aspect of the proposed approach is that both cell production rate and robot hardware limitations are considered as strict constraints, so that no plant revision is needed. The methodology relies on: a) calculation of energy-optimal trajectories, by means of time scaling, concerning the robots' motion from the last process point to the home positions; b) reduction of the energy consumption via earlier release of the actuator brake when the robots are kept stationary. Simulation results are presented, which are based on the production timing characteristics measured on a real plant. <s> BIB014 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> This paper proposes a novel cost function formulation for minimization of the energy consumption of industrial robots by trajectory optimization. Besides the dynamics of the robot including friction losses, the model especially takes into account the losses of servo drives and inverters. Furthermore, the ability of energy exchange between the robot axes via the coupled DC-bus is included, since the servo drives support generator mode during deceleration. The utilized energy-based robot model is applicable to different manipulator types. For the energy-efficient motion planning, point-to-point trajectories are defined by B-spline functions. The given nonlinear optimization problem is solved using gradient-based methods, considering kinematic and dynamic constraints. Several simulation results are presented, demonstrating the intense effect of energy exchange in the robot controller's power electronics. Furthermore, a comparative study is given showing that the proposed method is able to outperform existing torque-based approaches. <s> BIB015 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> In this paper, an minimum-energy point-to-point (PTP) trajectory is designed for a mechatronic system, which is a toggle mechanism driven by a permanent magnet synchronous motor (PMSM). To generate the PTP trajectory, we employ the real-coded genetic algorithm (RGA) to search for the minimum-absolute-energy trajectory for the mechatronic system. In this paper, a high-degree polynomial is used and the initial and final conditions (position, velocity, acceleration and jerk) are considered as the constraints for the trajectory. In the RGA method, the coefficients of the polynomial are determined by satisfying the desired fitness function of input absolute electric energy. The numerical simulations are compared between several degrees' polynomials during motion operation time for the toggle mechanism. <s> BIB016 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> In this paper, we propose a novel minimum-energy point-to-point (PTP) trajectory planning method for a motor-toggle servomechanism, which is described by the mathematical model of a mechatronic system. To generate the mechatronic trajectory, we employed the real-coded genetic algorithm (RGA) to search for the minimum-energy trajectory for the PTP motion profile, which is described by a polynomial with suitable conditions of position, velocity, and acceleration at the start and end points. The RGA algorithm determines the coefficients of polynomials with the fitness function of minimum-energy input, and is performed in numerical simulations and experiments. The results are compared with those of the S-curve by a traditional proportional-integral control. The proposed methodology can also be applied to any mechatronic system driven by a motor. <s> BIB017 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> Abstract The interest in novel methods and tools for optimizing the energy consumption in robotic systems is currently increasing. From an industrial point of view, it is desirable to develop energy saving strategies also applicable to established manufacturing systems with no need for either hardware substitution or further investments. Within this scenario, the present paper reports a method for reducing the total energy consumption of pick-and-place manipulators for given TCP position profiles. Firstly, electromechanical models of both serial and parallel manipulators are derived. Then, the energy-optimal trajectories are calculated, by means of constant time scaling, starting from pre-scheduled trajectories compatible with the actuation limits. In this manner, the robot work cycle can be energetically optimized also when the TCP position profiles have been already defined on the basis of technological constraints and/or design choices aimed at guaranteeing manufacturing process efficacy/robustness. The effectiveness of the proposed procedure is finally evaluated on two simulation case studies. <s> BIB018 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> Commonly, a modelling and simulation approach is used for parameter optimization and system behavior analysis of assembly system components. However, such simulation approaches are often not well integrated or its analysis is still based on a specific physical domain. This paper proposes an integrated simulation approach that can be used for designing, analyzing and optimizing the entire physical domain as well as the control system of mechatronic components in an assembly system. The state-of-the-art, requirements, our concept and the limitations of an integrated simulation approach are explained in this paper. A case study of the development of conveyor systems using the multi-domain simulation tool OpenModelica is also presented. On-going research shows that the integrated approach offers various benefits such as reduced development time and minimized errors, as well as maintenance during the commissioning process. <s> BIB019 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> This paper proposes a minimum energy trajectory planning method with residual vibration reduction for a robot manipulator mounted on flexible base, in which a point-to-point motion task of the manipulator is considered. In the proposed method, the joint angle of the robot manipulator is generated by radial basis function networks (RBFNs). The maximum residual vibration amplitude and operating energy are adopted as the objective functions, and then, the RBFNs are tuned by an elitist non-dominated sorting genetic algorithm (NSGA-II). The trajectory obtained using the proposed method can suppress the residual vibration of the flexible base in energy conservation. Results obtained from simulations reveal a trade-off relationship between the residual vibration amplitude and the operating energy. Furthermore, the validity of the proposed method is confirmed experimentally. <s> BIB020 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> The improvement of energy efficiency in automation and robotic systems still has high significance in engineering research. This paper presents experimental results of minimum energy trajectory optimization for multi-axis manipulators using electrical energy exchange via the shared inverter DC link. Thus, existing simulation findings demonstrating the potential of the proposed minimum energy optimization approach are validated. In this context, a global optimization method is applied utilizing an advanced cost function formulation that is based on an energy flow model including all servo drive components. After the validation of the utilized system model, increased efficiency improvements are proven and compared to established methods. The presented approach as well as the experimental results are fully transferable to any kind of multi-axis system comprising DC link energy supply. <s> BIB021 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> Abstract The elevator system driven by a permanent magnet synchronous motor (PMSM) is studied in this paper. The mathematical model of the elevator system includes the electrical and mechanical equations, and the dimensionless forms are derived for the purpose of practicable upward and downward movement. In this paper, the trapezoidal, cycloidal, five-degree (5-D) and seven-degree (7-D) polynomial and industry trajectories are designed and compared numerically in various motion and the absolute input energies. From numerical simulations, it is found that the trapezoidal trajectory consumes the minimum energy; the 7-D polynomial trajectory consumes the maximum one. The less end-point constraints are required, the less energy is consumed. Finally, the proposed sliding mode controller (SMC) is employed to demonstrate the robustness and well tracking control performance numerically. <s> BIB022 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> The energy demand of applications using in- verter controlled electrical servo drives is considerably de- pendent on the applied trajectory profiles. In this paper, the improvement potential in supply energy consumption is an- alyzed with respect to the standard servo controller func- tionality. The optimal choice of trajectory profiles and ex- ecution times for point-to-point movements offers distinct energy savings. From the presented results, a number of general trajectory parametrization advices of even roughly known system characteristics can be derived. Even with lit- tle effort and without knowledge of exact system parameters, considerable energy savings are achievable. <s> BIB023 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> This paper quantitatively reports about potential energy savings on robotic assembly lines for the automotive industry. At first, a detailed system model is described, which improves previously published results by explicitly considering both manipulator and electrical drive dynamics. The model closely captures experimental data in terms of actuation torques and servodrive voltages, which are directly used to derive the plant input power. Two practical methods are then evaluated for reducing the overall energy consumption. The methods rely on: 1) implementation of energy-optimal trajectories obtained by means of time scaling, concerning the robots' motion from the last process point to the home positions and 2) reduction of energy consumption by releasing the actuator brakes earlier when the robots are kept stationary. Simulation results, based on the production timing characteristics measured at a real plant, clearly shows that the system energy consumption can be effectively reduced without negative effects on the production rate. Note to Practitioners - The global industry trend towards sustainability demands energy optimization as a primary goal. Currently, industrial multirobot systems are not efficiently programmed as long as effective simulation tools are mostly lacking. In this context, a detailed model of the production line is proposed, which can be readily integrated into commercial tools for robot programming. Furthermore, the impact of practical optimization methods which are readily applicable to existing equipment is quantitatively highlighted. The key aspect of the proposed approach is that both the production rate of each cell and the robot hardware limitations are considered as strict constraints, so that no significant changes to the plant are required. <s> BIB024 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> Analyzing the mechatronic behavior of a manufacturing cell used in a customized manufacturing process is a difficult task with numerous obstacles. Therefore, a method that can be easily used for developing and optimizing a customized manufacturing cell, i.e., universal contacting module (UCM) cell, for the in-circuit testing of electronic modules is desired. In this paper, we present a convenient method using multi-domain simulation tools for analyzing the mechatronic behavior of the UCM cell. The UCM cell, which consists of mechatronic components such as a six-axis industrial robot and conveyor systems, were successfully modeled, simulated, and validated under several payloads. This work also presents a modeling procedure that can be applied by system engineers with a basic background in control systems for analyzing the mechatronic behavior of manufacturing cell components. <s> BIB025 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> Abstract The main idea of this paper is to design a novel point-to-point (PTP) trajectory based on minimum absolute input energy (MAIE) for an LCD glass-handing robot, which is driven by a permanent magnet synchronous motor (PMSM). The mechatronic system is described by a mathematical model of electrical and mechanical coupling equations. To generate the MAIE PTP trajectory, we employ a high-degree polynomial and compare with the trapezoidal, cycloidal and zero-jerk trajectories for various constraint conditions, which satisfy their corresponding desired constraints of angular displacement, speed, acceleration and jerk at the start and end times. The real-coded genetic algorithm (RGA) is used to search for the coefficients of high-degree polynomials for the PTP trajectories, and the inverse of absolute input electrical energy is adopted as a fitness function. From numerical simulations, it is found that either increasing the degree number of polynomials or decreasing the constraints at the start and end times will decrease the absolute input electrical energy. The proposed methodology for designing the MAIE PTP trajectory can also be applied to any mechatronic system driven by a PMSM. <s> BIB026 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> Abstract In this paper, energy-saving trajectories are planned for a toggle mechanism driven by a permanent magnet synchronous motor (PMSM). The point-to-point (PTP) trajectory is described by a high-degree polynomial, which satisfies the end conditions of displacement, velocity, acceleration and jerk at the initial and final times. The real-coded genetic algorithm (RGA) method is employed to obtain the mechatronic system’s parameters, and to determine the coefficients of the polynomial, and its fitness function is the inverse of various input energies. The numerical simulations and experiments are compared among several degrees’ polynomials during the whole operation motion. Finally, it is found that the input absolute electrical energy (IAEE) occurs when the highest-degree polynomial is chosen. From the percentage of relative error with respect to the absolute input energy of a 7-degree polynomial, it is found that the percentage of relative error achieves 32% as the degree is 24 with enough for minimum input energy degree. The proposed methodology described in this research has the contribution. It can be applied to any mechatronic system which is required to design a minimum-energy point to point trajectory. <s> BIB027 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> Abstract This paper presents a systematic methodology for on-site identification and energy-optimal path planning of an industrial robot. The identification experiments are carried out on-site, in a quick, non-invasive way using a CA8335 Qualistar three-phase electrical networks analyser. Next, the collected data is compared with a parametrised dynamic robot model in an optimisation routine. This routine results in the specification of a parametric dynamic robot model. The model is used as a dynamic constraint for a model predictive control problem, where other physical constraints are added i.e. the limited workspace and the constraints on the joint velocities and accelerations. A sequential quadratic programming solver is used to minimise a mechanical energy based cost function. The resulting energy-optimal path is translated into custom robot commands executable on an industrial robot. The systematic methodology is validated on an IRB1600 industrial ABB robot performing a custom pick-and- place operation. The obtained dynamic robot model is given and compared to the collected measurements. To demonstrate the possibility of energy saving by ‘intelligently’ programming a robot trajectory the energy and time-optimal paths are generated taking all physical constraints into account. Simulation results show a significant time and energy improvement (up to 5%) compared to most trajectories generated by the ABB software. The most remarkable result is that the fastest energy-optimal trajectory turns out to be 4% more energy efficient and 3% faster then the commercially available fastest trajectory. Additional stand-still experiments show that activation of the brakes is favoured over an actuated stand-still from an energy point of view, assuming that the start-up time when releasing the brakes is limited. <s> BIB028 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> Reducing the energy consumption of industrial robots (IR) that are used in manufacturing systems has become a main focus in the development of green production systems. This is due to the reality that almost all automated manufacturing processes are using IR as the main component. Thus, reducing the energy consumption of IR will automatically reduce operating costs and CO2 emissions. Therefore, a method for reducing the energy consumption of IR in manufacturing systems is desired. Firstly, this paper presents a literature survey of the research in energy consumption analysis of IR that is used in manufacturing processes. The survey found that current research in this field is focused on the development of simulation models of IR that are able to be used to predict its energy consumption. Secondly, a modular model to analyze power consumption and dynamic behavior of IR is developed. Afterward, an experimental investigation is carried out to validate and estimate the accuracy of the model developed. The investigation shows that the developed modular model can be conveniently used to optimize the industrial robot’s operating parameters, which are commonly needed for production planning and at the process optimization stage. In addition, the investigation shows that the process constraints, environment layout, productivity requirement, as well as the robot payload and operating speed are the key factors that must be considered for optimizing the productivity and efficiency of IR. <s> BIB029 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> This paper considers real-time energy-optimal trajectory generation for a servomotor system that performs a single-axis point-to-point positioning task for a fixed time interval. The servomotor system is subject to acceleration and speed constraints. The trajectory generation is formulated as a linear-constrained optimal control problem (LCOCP), and the Pontryagin's maximum principle is applied to derive necessary optimality conditions. Instead of solving multipoint boundary value problems directly, this paper proposes a novel real-time algorithm based on two realizations: solving the LCOCP is equivalent to determining an optimal time interval of the speed-constrained arc and solving a specific acceleration-constrained optimal control problem (ACOCP), and solving an ACOCP is equivalent to determining optimal switch times of acceleration-constrained arcs and solving a specific two-point boundary value problem (TBVP). The proposed algorithm constructs sequences of time intervals, ACOCPs, switch times, and TBVPs, such that all sequences converge to their counterparts of an optimal solution of the LCOCP. Numerical simulation verifies that the proposed algorithm is capable of generating energy-optimal trajectories in real time. Experiments validate that the use of energy-optimal trajectories as references in a servomotor system does not compromise tracking performance but leads to considerable less energy consumption. <s> BIB030 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> Abstract Among the techniques to improve energy efficiency of mechatronic systems, the synthesis of optimized motion profiles has been proved to be an effective and almost costless method. In order to boost the use of this approach, this paper proposes an analytical method for improving energy efficiency in rest-to-rest motion through optimal planning, by selecting both the optimal motion law and the optimal motion time (duration). The proposed technique is suitable for constant inertia systems. As a matter of fact, this kind of mechatronic systems covers a wide range of applications in production, packaging or logistic plants. The method practical application is straightforward, since it just relies on the knowledge of the task specifications and of some system parameters to compute the optimal motion time for each selected trajectory and to compare analytically different motion profiles. The limitations due the servo-actuator (torque, speed, bandwidth), to machine throughput requirements, as well as the smoothness specifications (acceleration and jerk limitations, degree of continuity) are explicitly accounted for through bounds, to ensure the feasibility of the motion profiles developed. Since the proposed method proposes an analytical algebraic equation, it does not require either time-consuming simulations and trial-and-error evaluations, or numerical optimizations. Hence, it is well suited for industrial mechatronic applications. <s> BIB031 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> The paper proposes an off-line robot motion planning approach, aimed at the reduction of the energy consumption, for any trajectory defined on a set of target points including some “fly” ones, i.e., points that must not be exactly reached by the robot. The proposed solution is based on the search for alternative paths close to the fly target points originally defined by the operator, and on the computation of the mechanical and total energy associated to each single possible motion defined for the generated alternative paths. A branch and bound algorithm is employed to scan all the possible motions and find the complete trajectory that corresponds to the minimum energy consumption. The approach has been implemented in a software architecture that exploits some COMAU software modules, but it could be easily adapted to generic, similar modules. The results that have been experimentally obtained for two typical industrial cycles, performed by a COMAU Racer robot, can be considered as very satisfying. <s> BIB032 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> Optimal trajectory planning for robot manipulators is always a hot spot in research fields of robotics. This paper presents a Constraint Immune Multi-objective Optimization Algorithm (CIMOA) for computing optimal trajectory of an industrial robot manipulator. The problem has a multi-criterion character in which two objectives, the minimum traveling time objective and minimum mechanical energy consumption objective are considered. In this paper, a model of trajectory planning for six-DOF manipulator based on CIMOA is established. With robot's mechanism system constraints, taking minimum traveling time and minimum energy as criterion, the robot trajectories are planned using CIMOA. Compared the results with single objective algorithm by genetic algorithm (GA) and weighted objective genetic algorithm (WGA), it is shown that, the travelling time and consuming energy by multiple objective method CIMOA are much less, and the trajectory in joint space is much smoother. <s> BIB033 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> Abstract This paper presents a proposal for a minimum energy feedforward control technique for flexible structures to suppress residual vibrations in point-to-point (PTP) motion. In the proposed method, the trajectory profile of the PTP motion is generated through a cycloidal function whose input is the output of a polynomial function. The obtained trajectory is dependent upon the coefficients of the polynomial function. To achieve the suppression of the residual vibration as well as the operating energy of this PTP motion, the coefficients are tuned by metaheuristic algorithms. In the numerical simulations, we investigated the PTP motions of a single-link flexible manipulator and a robotic arm attached to a flexible link. The simulation results were compared with those of previous studies, revealing the effectiveness of the proposed method. <s> BIB034 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> Abstract: This paper presents an optimization technique to develop minimum energy consumption trajectories for redundant/hyper-redundant manipulators with pre-defined kinematic and dynamic constraints. The optimization technique presents and combines two novel methods for trajectory optimization. In the first method, the system’s kinematic and dynamics constraints are handled in a sequential manner within the cost function to avoid running the inverse dynamics when the constraints are not satisfied. Thus, the complexity and computational effort of the optimization algorithm is significantly reduced. For the second method, a novel virtual link concept is introduced to replace all the redundant links to eliminate physical impossible configurations before running the inverse dynamic model for the trajectory optimization. The method is verified on a three-degree-of-freedom redundant manipulator. <s> BIB035 </s> A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems <s> Software: Enhancement of the Motion Planning Phase <s> The exact solution of practical trajectory optimization problems are usually not feasible in real time. The use of approximate solutions deduced form a nominal optimal solution is a potential alternative. This requires evaluation of parametric sensitivities of the nominal solution in real time. This is addressed in this paper. Improvements to existing methods are introduced that not only increase their efficiency but also ensure the constraint satisfaction of the approximation. The proposed methods are applied to a practical trajectory planning problem for a planar manipulator where the initial state is given but the final state is unknown prior to task execution. <s> BIB036
The software approach relies on the modification and optimization of the motion planning phase of a mechatronic system. The first step of the general workflow of the software approach is the definition of a suitable system model: this is exploited to perform simulations and the analysis of different strategies, through the evaluation of the energy consumption and the dynamic behavior of the mechatronic system  . In literature, different approaches are used to build the model; it can be defined through a mathematical formulation and by considering only the main important factors (i.e., basic mathematical model) , or it is possible to also take into account secondary terms that increase the results' precision but on the other hand need more computational efforts (i.e., extended mathematical model) BIB022 BIB023 BIB031   BIB014 BIB024 . The availability of software simulation tools allows thus the simple implementation of complex extended models BIB018 BIB032 BIB033  that can describe several physical domains   BIB019 BIB029 BIB025 . These allow for the integration of several simulation approaches that are evaluated separately: control, kinematic, dynamic, physical behavior, and discrete event simulations BIB019 . The workflow proceeds with the assignment of the system parameters, such as links' lengths, masses, actuator electrical parameters, and so forth. These can be retrieved by datasheets, the CAD model, estimation, or eventually direct or indirect measurements of the system. Then, a comparative analysis with a real system is generally performed to validate the overall dynamic model and possibly to improve it  . The system model is thus then ready to be exploited for testing the software optimization strategies. Different solutions relying on the software approach have been published; see Table 2 . All of these can be divided into two main subcategories: 1. Trajectory optimization: A modification of the path or the motion profile, or both, are performed. 2. Operation scheduling: Re-scheduling of subsequent movements and operations is considered. BIB023 2014 Conference paper Trajectroy optimization PTP-direct Generic mechatronic system (1 DoF)  2010 Conference paper Trajectroy optimization PTP-direct Serial robot (6 DoFs) BIB029 2010 Journal paper Trajectroy optimization PTP-direct Serial robot (6 DoFs) BIB025 2014 Journal paper Trajectroy optimization PTP-direct Serial robot (6 DoFs) BIB031 2016 Journal paper Trajectroy optimization PTP-direct Mechatronic system (1 DoF)-constant inertia  2012 Journal paper Trajectroy optimization PTP-direct Storage and retrieval vehicle (2 DoFs)  2013 Journal paper Trajectroy optimization PTP-direct Storage and retrieval vehicle (2 DoFs) BIB020 2013 Conference paper Trajectroy optimization PTP-inverse Serial robot (1 DoF) mounted on a flexible base BIB034 2016 Journal paper Trajectroy optimization PTP-inverse Serial robot (1 DoF) mounted on a flexible base BIB035 2016 Journal paper Trajectroy optimization PTP-inverse Redundant serial robot (3 DoFs) BIB007 2010 Conference paper Trajectroy optimization PTP-inverse Serial robot (6 DoFs)  2015 Conference paper Trajectroy optimization PTP-inverse Mechatronic system (1 DoF)-linear axis BIB001 1996 Conference paper Trajectroy optimization PTP-inverse Serial robot (6 DoFs) BIB008 2011 Journal paper Trajectroy optimization PTP-inverse Underactuated serial kinematics BIB009 2011 Conference paper Trajectroy optimization PTP-inverse Underactuated serial kinematics BIB026 2014 Journal paper Trajectroy optimization PTP-inverse Underactuated serial kinematics BIB021 2013 Conference paper Trajectroy optimization PTP-inverse Generic mechatronic system (2 DoFs) BIB015 2012 Conference paper Trajectroy optimization PTP-inverse Serial robot (6 DoFs)  2012 Conference paper Trajectroy optimization PTP-inverse Generic mechatronic system (1 DoF) BIB010 2011 Conference paper Trajectroy optimization PTP-inverse Mechatronic system (1 DoF)-positoning table BIB016 2012 Conference paper Trajectroy optimization PTP-inverse Mechatronic system (1 DoF)-toggle mechanism BIB027 2014 Journal paper Trajectroy optimization PTP-inverse Mechatronic system (1 DoF)-toggle mechanism BIB011 2011 Conference paper Trajectroy optimization PTP-inverse Mechatronic system (1 DoF)-positioning table BIB017 2012 Journal paper Trajectroy optimization PTP-inverse Mechatronic system (1 DoF)-toggle mechanism BIB012 2011 Conference paper Trajectroy optimization PTP-inverse Generic mechatronic system (2 DoFs) BIB006 2006 Conference paper Trajectroy optimization PTP-inverse Redundant serial robot (3 DoFs) BIB002 1996 Journal paper Trajectroy optimization PTP-inverse Generic mechatronic system (1 DoF) BIB004 2002 Conference paper Trajectroy optimization PTP-inverse Generic mechatronic system (1 DoF) BIB030 2015 Journal paper Trajectroy optimization PTP-inverse Generic mechatronic system (1 DoF) BIB005 2004 Conference paper Trajectroy optimization PTP-inverse Flexible links robot (2 links) BIB036 2017 Conference paper Trajectroy optimization PTP-inverse Redundant serial robot (4 DoFs) BIB022 2016 Conference paper Trajectroy optimization Multi-point Serial robot (6 DoFs) BIB033 2016 Conference paper Trajectroy optimization Multi-point Serial robot (6 DoFs) BIB003 1997 Conference paper Trajectroy optimization Multi-point Redundant serial robot (3 DoFs)  2014 Conference paper Trajectroy optimization Multi-point Serial robot (6 DoFs) BIB028 2014 Conference paper Trajectroy optimization Multi-point Serial robot (6 DoFs) BIB013 2011 