Motion Planning for a Humanoid Mobile Manipulator System

Abstract

A high redundant non-holonomic humanoid mobile dual-arm manipulator system (MDAMS) is presented in this paper where the motion planning to realize "humanlike" 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 online 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 (MOGA) is proposed to design the "human-like" viaposes by optimizing four objective functions. Finally, numerous simulations are presented to validate the effectiveness of proposed algorithms.

A Gradient Neural Network for online Solving the Time-varying Inverse Kinematics Problem of Four-wheel Mobile Robotic Arm

“…As one of the typical structures of mobile robots, the mobile robotic arm is constituted of a mobile platform and a robotic arm fastened on the mobile platform. In this way, the mobile robotic arm has the dual properties of the vastness of the working space of the mobile robot and the flexibility of the operating space of the robot [4][5][6]. According to the movement form, the mobile robotic arm can be divided into four types: wheeled mobile robotic arm, crawler mobile robotic arm, leg mobile robotic arm and hybrid mobile robotic arm.…”

Subplanner Algorithm to Escape from Local Minima for Artificial Potential Function Based Robotic Path Planning

“…This problem is often solved by a combination of computational geometry, heuristic search algorithms, and game-theoretic decision-making [1,4,5]. The applications of the robotic path planning have been explored in a broad range of field such as mobile robots [6][7][8], aerial robots [9,10], fork-type lifters [11,12], humanoid robot [13,14], etc.…”