Motion planning for mobile robots using inverse kinematics branching

Abstract

A novel algorithm for planning robotic manipulation tasks is presented in which the base position and joint motions of a robot are simultaneously optimized to follow a smooth desired end-effector trajectory. During the optimization routine, the manipulator's base position and joint motions are planned simultaneously by strategically moving a set of virtual robot arms (each representing a single configuration in a sequence) branching from a common base to a number of assigned target poses associated with a task. Additional goals (e.g. collision avoidance) and hard constraints, including joint limits are also incorporated. The optimization problem at the core of this method is a quadratic program, allowing constrained high-dimensional problems to be solved in very little time. This method has successfully planned motions allowing an 8-DOF manipulator to paint walls, and has proven to be highly efficient and scalable in practice.