Overview

Some of the most significant challenges confronting autonomous robotics lie in the area of automatic motion planning. The goal is to be able to specify a task in a high-level language and have the robot automatically compile this specification into a set of low-level motion primitives, or feedback controllers, to accomplish the task. The prototypical task is to find a path for a robot, whether it is a robot arm, a mobile robot, or a magically free-flying piano, from one configuration to another while avoiding obstacles. From this early piano mover's problem, motion planning has evolved to address a huge number of variations on the problem, allowing applications in areas such as animation of digital characters, surgical planning, automatic verification of factory layouts, mapping of unexplored environments, navigation of changing environments, assembly sequencing, and drug design. New applications bring new considerations that must be addressed in the design of motion planning algorithms.

Since actions in the physical world are subject to physical laws, uncertainty, and geometric constraints, the design and analysis of motion planning algorithms raises a unique combination of questions in mechanics, control theory, computational and differential geometry, and computer science. The impact of automatic motion planning, therefore, goes beyond its obvious utility in applications. The possibility of building computer-controlled mechanical systems that can sense, plan their own motions, and execute them has contributed to the development of our math and science base by asking fundamental theoretical questions that otherwise might never have been posed.

This book...