Aiming at such problems as unknown goal configuration, grasp space limitation, a large number of barriers in configuration space and high-dimension space redundancy during planning motion of humanoid robot arms graspi...
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ISBN:
(纸本)9781510817371
Aiming at such problems as unknown goal configuration, grasp space limitation, a large number of barriers in configuration space and high-dimension space redundancy during planning motion of humanoid robot arms grasping target, this paper proposes a generalized inverse rapid-exploringrandomtree(GIRRT) collision avoidance method. Firstly, it establishes kinematics and inverse kinematics models for upper arm of humanoid robot based on hierarchical sub-dimension space motion planning concept model. Secondly, it proposes a weighted minimal norm GIRRT planning algorithm. Finally, the effectiveness of the algorithm proposed in this paper has been verified via computer 3D simulation.
For a biped climbing robot with dual grippers to climb poles, trusses or trees, feasible collision-free climbing motion is inevitable and essential. In this paper, we utilize the sampling-based algorithm, Bi-RRT, to p...
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For a biped climbing robot with dual grippers to climb poles, trusses or trees, feasible collision-free climbing motion is inevitable and essential. In this paper, we utilize the sampling-based algorithm, Bi-RRT, to plan single-step collision-free motion for biped climbing robots in spatial trusses. To deal with the orientation limit of a 5-DoF biped climbing robot, a new state representation along with corresponding operations including sampling, metric calculation and interpolation is presented. A simple but effective model of a biped climbing robot in trusses is proposed, through which the motion planning of one climbing cycle is transformed to that of a manipulator. In addition, the pre- and post-processes are introduced to expedite the convergence of the Bi-RRT algorithm and to ensure the safe motion of the climbing robot near poles as well. The piecewise linear paths are smoothed by utilizing cubic B-spline curve fitting. The effectiveness and efficiency of the presented Bi-RRT algorithm for climbing motion planning are verified by simulations.
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