Manipulator path planning in 3-dimensional space

Dmitry A. Pavlov

doi:10.1117/12.676736

9 June 2006 Manipulator path planning in 3-dimensional space

Dmitry A. Pavlov

Proceedings Volume 6253, Ninth International Workshop on Nondestructive Testing and Computer Simulations; 62530P (2006) https://doi.org/10.1117/12.676736
Event: Ninth International Workshop on Nondestructive Testing and Computer Simulations, 2005, St. Petersburg, Russian Federation

Abstract

Present paper is aimed to work out efficient algorithm of multi-chain manipulator path planning in 3D space with static polygonal obstacles. The resulting solution is based on navigational maps approach. Using this approach, manipulator features are considered as intellectual agent, and reachability information is stored in compact form. This enables fast adaptation to arbitrary parameters of manipulator and workspace. The paper describes two algorithms: (i) a local walkthrough with obstacle avoidance, and (ii) incremental navigational map building, performed at running stage. Both algorithms take an extensive use of the specific features of the task. Working simultaneously, they allow real-time manipulator path planning, as well as self-learning in idle mode. Algorithms are implemented as a demonstration program.

Citation Download Citation

Dmitry A. Pavlov "Manipulator path planning in 3-dimensional space", Proc. SPIE 6253, Ninth International Workshop on Nondestructive Testing and Computer Simulations, 62530P (9 June 2006); https://doi.org/10.1117/12.676736

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

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