Survey: Motion Planning Algorithms by Leslie Glaves
[email protected] CSE638 Topics in Computational Geometry Professor Joe Mitchell Stony Brook University, New York 11794 May 2004 Abstract This paper introduces and surveys current progress in path/motion planning al- gorithms with greater attention given to recent work with RRTs (Rapidly-Exploring Random Trees). 1 Introduction The perennial pursuit of artificial intelligence, that of constructing a robot that can learn on it’s own can be distilled to solving a few essential problems. For a mobile robot, a basic problem is how to plan to move, alternately referred to as path planning or motion planning. Although robotic applications are currently one of the most popular and highly publicized topics in motion planning, planning and solving collision free paths is required for many other computational pursuits. Motion planning is used in graphic animation and video game software, navigation within virtual environments, physics-based simulation, CAGD (computer-aided geometric design), molecular dynamics (such as binding and folding), vir- tual prototyping, computer controlled medical surgery and for computerized navigation of all types of vehicles (wheeled, aircraft, spacecraft, etc). Study of motion planning is encom- passed by several disciplines, including (but not limited to): Computer Science, Artificial Intelligence, Robotics, Mechanical Engineering, Computational Geometry and Differential Geometry. 1 The most basic motion planning problem is to compute a collision-free path from start loca- tion to goal location in a static environment containing obstacles which must be manuvered around. In reality, motion planning often involves reaching a goal location while obstacles are moving in the environment and optimized paths are desired.