Kinematic modeling of a RHex-type robot using a neural network

Mario Harper; James Pace; Nikhil Gupta; Camilo Ordonez; Emmanuel G. Collins Jr.

doi:10.1117/12.2262894

5 May 2017 Kinematic modeling of a RHex-type robot using a neural network

Mario Harper, James Pace, Nikhil Gupta, Camilo Ordonez, Emmanuel G. Collins Jr.

Proceedings Volume 10195, Unmanned Systems Technology XIX; 1019507 (2017) https://doi.org/10.1117/12.2262894
Event: SPIE Defense + Security, 2017, Anaheim, CA, United States

Abstract

Motion planning for legged machines such as RHex-type robots is far less developed than motion planning for wheeled vehicles. One of the main reasons for this is the lack of kinematic and dynamic models for such platforms. Physics based models are difficult to develop for legged robots due to the difficulty of modeling the robot-terrain interaction and their overall complexity. This paper presents a data driven approach in developing a kinematic model for the X-RHex Lite (XRL) platform. The methodology utilizes a feed-forward neural network to relate gait parameters to vehicle velocities.

Conference Presentation

Citation Download Citation

Mario Harper, James Pace, Nikhil Gupta, Camilo Ordonez, and Emmanuel G. Collins Jr. "Kinematic modeling of a RHex-type robot using a neural network", Proc. SPIE 10195, Unmanned Systems Technology XIX, 1019507 (5 May 2017); https://doi.org/10.1117/12.2262894

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