Robot trajectory planning using a genetic algorithm

Daniel J. Pack; Gregory J. Toussaint; Randy L. Haupt

doi:10.1117/12.258129

Abstract

In this paper, we studied the trajectory generation problem for a two-degrees-of-freedom robot in a workspace with obstacles. To generate the robot's trajectories, we developed a genetic algorithm to search for valid solutions in the configuration space. Our results present a novel perspective on the problem not seen in the conventional robot trajectory planners. The genetic algorithm approach is beneficial because it may be extended to plan trajectories for robots with more degrees of freedom. The evolutionary search process may allow the user to solve the trajectory problem in an n-dimensional space where the 'curse of dimensionality' inevitably stalls conventional methods. We demonstrate the algorithm with some examples and discuss the possible extension to higher order problems.

Citation Download Citation

Daniel J. Pack, Daniel J. Pack, Gregory J. Toussaint, Gregory J. Toussaint, Randy L. Haupt, Randy L. Haupt, } "Robot trajectory planning using a genetic algorithm", Proc. SPIE 2824, Adaptive Computing: Mathematical and Physical Methods for Complex Environments, (11 November 1996); doi: 10.1117/12.258129; https://doi.org/10.1117/12.258129

ACCESS THE FULL ARTICLE

PERSONAL SIGN IN
Full access may be available with your subscription

Email or Username Forgot your username?

Password Forgot your password?

Show

Remember Email/Username on this computer

Remember Password

No SPIE account? Create an account
or Institutional Sign In via Shibboleth

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $14.40

Non-members: $18.00 ADD TO CART

Show All Keywords

Keywords/Phrases

Search In:

Publication Years