In this work, we address traffic management of multiple payload transport systems comprising of non-holonomic robots. We consider loosely coupled rigid robot formations carrying a payload from one place to another. Each payload transport system (PTS) moves in various kinds of environments with obstacles. We ensure each PTS completes its given task by avoiding collisions with other payload systems and obstacles as well. Each PTS has one leader and multiple followers and the followers maintain a desired distance and angle with respect to the leader using a decentralized leader-follower control architecture while moving in the traffic. We showcase, through simulations the time taken by each PTS to traverse its respective trajectory with and without other PTS and obstacles. We show that our strategies help manage the traffic for a large number of PTS moving from one place to another.
Over the years, various methods have been developed for formation control and navigation of formations for payload transportation. @cite_23 , @cite_11 propose methods for path planning of a single formation without laying much emphasis on the presence of obstacles. @cite_10 , @cite_3 , @cite_25 , @cite_4 shows navigation of single formation in environments which consists of static obstacles.Path planning for 3D formations is proposed in @cite_17 and @cite_24 . Method for navigating a single formation using the leader-follower approach is shown in @cite_25 and @cite_7 . @cite_20 , @cite_15 shows some promising results in aerial vehicle formation control. A slung payload transportation method is demonstrated in @cite_18 where as @cite_9 devised wheeled locomotion for payload carrying with modular robot. @cite_19 proposes path planning of a single formation in environment with dynamic obstacles but is a computationally expensive centralized method.
@cite_18 @cite_4 @cite_7 @cite_9 @cite_17 @cite_3 @cite_24 @cite_19 @cite_23 @cite_15 @cite_10 @cite_25 @cite_20 @cite_11
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An approach for coordination and control of 3D heterogeneous formations of unmanned aerial and ground vehicles under hawk-eye-like relative localization is presented in this paper. The core of the method lies in the use of visual top-view feedback from flying robots for the stabilization of the entire group in a leader-follower formation. We formulate a novel model predictive control-based methodology for guiding the formation. The method is employed to solve the trajectory planning and control of a virtual leader into a desired target region. In addition, the method is used for keeping the following vehicles in the desired shape of the group. The approach is designed to ensure direct visibility between aerial and ground vehicles, which is crucial for the formation stabilization using the hawk-eye-like approach. The presented system is verified in numerous experiments inspired by search-and-rescue applications, where the formation acts as a searching phalanx. In addition, stability and convergence analyses are provided to explicitly determine the limitations of the method in real-world applications. This work presents a path planning algorithm for 3D robot formations based on the standard Fast Marching Square (FM2) path planning method. This method is enlarged in order to apply it to robot formations motion planning. The algorithm is based on a leader-followers scheme, which means that the reference pose for the follower robots is defined by geometric equations that place the goal pose of each follower as a function of the leader's pose. Besides, the Frenet-Serret frame is used to control the orientation of the formation. The algorithm presented allows the formation to adapt its shape so that the obstacles are avoided. Additionally, an approach to model mobile obstacles in a 3D environment is described. This model modifies the information used by the FM2 algorithm in favour of the robots to be able to avoid obstacles. The shape deformation scheme allows to easily change the behaviour of the formation. Finally, simulations are performed in different scenarios and a quantitative analysis of the results has been carried out. The tests show that the proposed shape deformation method, in combination with the FM2 path planner, is robust enough to manage autonomous movements through an indoor 3D environment. The objective of this paper is to develop a vision-based navigation technique for micro aerial vehicles, quadrotor type, to operate in GPS-denied environment. The navigation method has been developed while using appearance-based Visual-Teach-and-Repeat (VT&R) technique. In a teaching phase, a quadrotor is manually navigated along a desired route to collect a set of reference images. In a repeating phase, the quadrotor is able to autonomously follow the desired route using these reference images. Self-localization is developed to determine the current segment of the desired route by a number of Speeded-Up Robust Features (SURF), matched between the current image and the reference images. In this paper, three methods of self-localization are proposed and compared. After performing self-localization, the quadrotor computes appearance-based motion control commands (desired yaw and height) for the next movement in order to keep track of the desired route. This computation is developed on Funnel Lane theory, which was originally proposed in Chen and Birchfield (IEEE Trans. Robot. 25(3), 749---754 (11)) for 2D navigation of a ground vehicle. The paper extends this theory to 3D navigation of a quadrotor.The proposed self-localization methods are tested with several image databases. Finally, an online experiment of proposed VT&R technique is demonstrated using Ar.Drone quadrotor model. Potential-field-based control strategy for path planning and formation control of multi Quadrotor systems is proposed in this work. The potential field is used to attract the Quadrotor to the goal location as well as avoiding the obstacle. The algorithm to solve the so called local minima problem by utilizing the wall-following behavior is also proposed. The resulted path planning via potential function strategy is then used to design formation control algorithm. Using the virtual leader approach, the formation control strategy by means of potential function is formulated. Each Quadrotor is assigned attractive potential to reach its desired position in formation. Each Quadrotor is also treated as moving obstacle which induces repulsive potential to the others in order to prevent inter-robot collision. The desired position for each Quadrotor in certain configuration is calculated based on the virtual leaderâ��s current position. To get smooth movement, the virtual leader is set as unicycle robot. The repulsive potential is also attached to each agent in case it moves in the region inside the obstacleâ��s influence. The overall strategy has been successfully applied to the Quadrotorâ��s model of Parrot AR Drone 2.0 in Gazebo simulator programmed using Robot Operating System.