Journal
UNMANNED SYSTEMS TECHNOLOGY XIX
Volume 10195, Issue -, Pages -Publisher
SPIE-INT SOC OPTICAL ENGINEERING
DOI: 10.1117/12.2262894
Keywords
Legged Robots; Kinematic Modeling; Neural Network
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Funding
- U.S. Army Research Laboratory under the Collaborative Technology Alliance Program [DAAD 19-01-2-0012]
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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.
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