A hyper-redundant robotic arm is a manipulator with many degrees of freedom, capable of executing tasks in cluttered environments where robotic arms with fewer degrees of freedom are unable to operate. This paper introduces a new method for modeling those manipulators in a completely dynamic way. The proposed method enables online changes of the kinematic structure with the use of a special function; termed “meta-controlling function”. This function can be used to develop policies to reduce drastically the computational cost for a single task, and to robustly control the robotic arm, even in the event of partial damage. The direct and inverse kinematics are solved for a generic three-dimensional articulated hyperredundant arm, that can be used as a proof of concept for more specific structures. To demonstrate the robustness of our method, experimental simulation results, for a basic “meta-controlling” function, are presented.
There are many technical difficulties arising from having big open-chained kinematic structures because of the exponential increment of the splines forces at the joints to all the body. This problem prohibited the application of the first hyper redundant manipulators in three-dimensional space. For example studies such as the one by Chirikjian and Burdick @cite_29 used a 2 dimensional arms with 30 degrees of freedom. There are some solutions that have been proposed addressing some of those technical difficulties such as studies that focus on building hyper redundant robotic arms @cite_3 @cite_17 @cite_23 @cite_18 @cite_34 @cite_19 , and studies that deal with the design of joints with many DoFs per joint, used for hyper redundant arms @cite_32 @cite_5 @cite_30 . by @cite_3 , @cite_17 , @cite_23 , @cite_18 , and @cite_34 , and @cite_19 that focus on building hyper redundant robotic arms. Other studies by @cite_32 , @cite_5 and @cite_30 deal with the structure of joints of many DoFs that used for hyper redundant arms.
@cite_30 @cite_18 @cite_29 @cite_32 @cite_3 @cite_19 @cite_23 @cite_5 @cite_34 @cite_17
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In this paper we consider the motion planning problem of humanoid with articulated-spine for object manipulation in double support phase. Complexity of motion planning increases due to higher degrees-of-freedom (DOF), redundancy arising due to articulated spine, inherent underactuation and stability constraint. Additionally, loop-closure constraints arise during double-support phase, and self-collision constraints exist independent of the task to be performed. These problems make motion planning of humanoids a challenging task. In this work, we address the above issues by proposing a sampling based approach for planning the motion of the humanoid. Our approach to the problem is based on RRT* which can generate asymptotically optimal paths. The proposed approach deals with the stability constraints by rejective sampling approach which divides random configurations generated into valid and invalid configurations. Additionally, the loop-closure constraints are tackled by separating the humanoid into two open-kinematic sub-chains, and then generating random configurations in one sub-chain whereas the remaining sub-chain uses inverse kinematics for closure. Efficacy of the proposed approach is demonstrated for whole-body motion planning of a 25-DOF humanoid in generating asymptotically optimal end-effector paths. We present a novel 6-DoF cable driven manipulator for handheld robotic tasks. Based on a coupled tendon approach, the arm is optimized to maximize movement speed and configuration space while reducing the total mass of the arm. We propose a space carving approach to design optimal link geometry maximizing structural strength and joint limits while minimizing link mass. The design improves on similar non-handheld tendon-driven manipulators and reduces the required number of actuators to one per DoF. As the manipulator has one redundant joint, we present a 5-DoF inverse kinematics solution for the end effector pose. The inverse kinematics is solved by splitting the 6-DoF problem into two coupled 3-DoF problems and merging their results. A method for gracefully degrading the output of the inverse kinematics is described for cases where the desired end effector pose is outside the configuration space. This is useful for settings where the user is in the control loop and can help the robot to get closer to the desired location. The design of the handheld robot is offered as open source. While our results and tools are aimed at handheld robotics, the design and approach is useful to non-handheld applications. The term "hyper-redundant" refers to robotic manipulators and mobile robots with a very large, possibly infinite, number of actuatable degrees of freedom. These robots are analogous in morphology and operation to snakes, worms, elephant trunks, and tentacles. This thesis presents a novel kinematic framework for hyper-redundant manipulator motion planning and task implementation. The basis of this formulation is the use of a "backbone reference set" which captures the essential macroscopic geometric features of hyper-redundant robots. In the analytical part of this work, the backbone representation is developed and used to solve problems in obstacle avoidance, locomotion, grasping, and "optimal" end effector placement. The latter part of this thesis deals with the design and implementation of a thirty-degree-of-freedom planar hyper-redundant manipulator which is used to demonstrate these novel kinematic and motion planning techniques. Design issues such as robustness with respect to mechanical failure, and design for easy assembly and repair are also addressed. The analytical and design concepts are combined to illustrate tasks for which hyper-redundant robotic mechanisms are well suited. In this paper, the kinematics of a joint with three degrees of freedom for a novel hyper-redundant robot arm is investigated. This joint is able to achieve a superposed rotation about two axes (roll and pitch) and a translational motion along one axis as a common prismatic joint. The forward and inverse kinematics of the so-called Multi-Joint will be determined in a closed-form solution. Next, the reachable and suitable workspace will be worked out to determine the solution space of the inverse kinematics. Finally, the differential kinematics to compute the cartesian velocity and statics will be determined.