Title: Motion Planning for a Humanoid Mobile Manipulator System,
Abstract: A high redundant non-holonomic humanoid mobile dual-arm manipulator system is
presented in this paper where the motion planning to realize "human-like"
autonomous navigation and manipulation tasks is studied. Firstly, an improved
MaxiMin NSGA-II algorithm, which optimizes five objective functions to solve
the problems of singularity, redundancy, and coupling between mobile base and
manipulator simultaneously, is proposed to design the optimal pose to
manipulate the target object. Then, in order to link the initial pose and that
optimal pose, an off-line motion planning algorithm is designed. In detail, an
efficient direct-connect bidirectional RRT and gradient descent algorithm is
proposed to reduce the sampled nodes largely, and a geometric optimization
method is proposed for path pruning. Besides, head forward behaviors are
realized by calculating the reasonable orientations and assigning them to the
mobile base to improve the quality of human-robot interaction. Thirdly, the
extension to on-line planning is done by introducing real-time sensing,
collision-test and control cycles to update robotic motion in dynamic
environments. Fourthly, an EEs' via-point-based multi-objective genetic
algorithm is proposed to design the "human-like" via-poses by optimizing four
objective functions. Finally, numerous simulations are presented to validate
the effectiveness of proposed algorithms.