An approach for coordinating mobility and manipulation

Abstract

This paper addresses the problem of planning a task for a robotic system comprised of a manipulator mounted on a mobile base. The task planning problem is formulated as a nonlinear optimization problem. The cost of point-to-point motion in three-dimensional Cartesian space is decomposed into two components representing the qualitative difference between motion due to the mobile base and motion due to the manipulator system. Task specifications at each end of the motion impose constraints on the endpoint configurations. The resulting regions of feasible positions and configurations are unconnected and nonconvex. Thus, standard algorithms for nonlinear optimization lead to nonextremal solutions. We present a heuristic method for searching a tree of starting points for a standard numerical algorithm to find a global minimum for the cost function. The problem formulation is illustrated for a 3 degrees-of-freedom (DOF) manipulator on a simple 2 DOF mobile base and trade-offs between base motion and manipulator motion are evaluated with respect to cost function weighting coefficients.

Mobile manipulation with a kinematically redundant manipulator for a pick-and-place scenario

“…An example of motion coordination is given in [5], where the coordination problem is formulated as a nonlinear optimization problem. The result is evaluated on a two degreesof-freedom mobile base combined with a three degrees-offreedom manipulator.…”

Redundancy coordination of multiple robotic devices for welding through genetic algorithm

“…In this paper, we have developed another robust technique, Genetic Algorithm, to solve the path-planning problem for the redundancy manipulator system used by Min Zhao 5 and W. Carriker. 7 The welding is to be carried out in a down-handed convention to allow the plasma to flow appropriately along the weld contour. This requires the weld piece surface to be anti-parallel to the gravity direction throughout the entire welding process.…”

“…However, the number of initial guesses grows rapidly with the number of tasks. An improvement 7 is to generate new initial points based on the results of previous executions of the numerical optimization algorithm.…”

Manipulation of a Mobile Modular Manipulator Interacting With the Environment With the Assistance of Tactile Sensing Feedback

“…Yamamoto and Yun 10,11 studied the effect of the dynamic interactions between the manipulator and the mobile platform of a mobile manipulator on the task performance and then developed a nonlinear feedback that completely compensated the dynamic interaction. Yu 14 decomposed the cost of pointto-point motion in three-dimensional (3D) Cartesian space into two components representing the qualitative difference between the motion caused by the mobile base and the motion caused by the manipulator system. This paper is organized as follows.…”