Motion Planning and Obstacle Avoidance

  • Javier Minguez
  • Florant Lamiraux
  • Jean-Paul Laumond

Abstract

This chapter describes motion planning and obstacle avoidance for mobile robots. We will see how the two areas do not share the same modeling background. From the very beginning of motion planning, research has been dominated by computer sciences. Researchers aim at devising well-grounded algorithms with well-understood completeness and exactness properties.

The challenge of this chapter is to present both nonholonomic motion planning (Sects. 47.147.6) and obstacle avoidance (Sects. 47.747.10) issues. Section 47.11 reviews recent successful approaches that tend to embrace the whole problem of motion planning and motion control. These approaches benefit from both nonholonomic motion planning and obstacle avoidance methods.

3-D

three-dimensional

DD

differentially driven

DWA

dynamic window approach

HSGR

high safety goal

HSWR

high safety wide region

IJCAI

International Joint Conference on Artificial Intelligence

LARC

Lie algebra rank condition

ND

nearness diagram navigation

ORM

obstacle restriction method

PFM

potential field method

PRM

probabilistic roadmap method

RRT

rapidly exploring random tree

RS

Reeds and Shepp

VFH

vector field histogram

VO

velocity obstacle

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Javier Minguez
    • 1
  • Florant Lamiraux
    • 2
  • Jean-Paul Laumond
    • 2
  1. 1.Department of Computer Science and Systems EngineeringUniversity of ZaragozaZaragozaSpain
  2. 2.LAAS-CNRSToulouseFrance

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