Paper
23 January 1997 Intelligent control of a simulated running jointed leg
Peggy Israel Doerschuk, Vihn Nguyen, Mani Venkatesh, Faqiang Kwong, Andrew Li
Author Affiliations +
Abstract
We present a modular approach to intelligent control of a simulated jointed leg in performing the task of running. The modular controller learns from experience to generate the appropriate control signals. We focus on the control of a single running stride. Separate controllers are used for each of three phases of the stride. A neurofuzzy takeoff controller produces torques which are applied at the leg joints while the foot is on the ground. It controls the height, distance and angular momentum of the stride. Once the foot leaves the ground, a neural network based controller is used to control the movement of the leg during the ballistic phase. This controller moves the joints along a planned trajectory which avoids obstacles, if any, and places the leg in an appropriate configuration for landing. When the foot touches the ground, a neural network based landing controller takes over. It is designed to produce control torques which will move the leg into a crouched position suitable for takeoff of the next stride. Results achieved by the takeoff and ballistic controllers are presented here. Very accurate control is achieved for simple strides of different sizes and strides which involve scaling an obstacle.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Peggy Israel Doerschuk, Vihn Nguyen, Mani Venkatesh, Faqiang Kwong, and Andrew Li "Intelligent control of a simulated running jointed leg", Proc. SPIE 2903, Mobile Robots XI and Automated Vehicle Control Systems, (23 January 1997); https://doi.org/10.1117/12.265333
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KEYWORDS
Prototyping

Device simulation

Neural networks

Tellurium

Motion controllers

Selenium

Fuzzy logic

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