An approach for coordinating mobility and manipulation

Abstract

The authors discuss the problem of planning a task for a robotic system that consists 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. A heuristic method is presented 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 three-degrees-of-freedom (DOF) manipulator on a simple two-DOF mobile base, and tradeoffs between base motion and manipulator motion are evaluated with respect to cost function weighting coefficients.