Soft computing-based expert systems to predict energy consumption and stability margin in turning gaits of six-legged robots

Authors:
Shibendu Shekhar Roy;Dilip Kumar Pratihar
Affiliations:
Department of Mechanical Engineering, National Institute of Technology, Durgapur, India;Department of Mechanical Engineering, Indian Institute of Technology, Kharagpur, India
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

Citing 6
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Machines That Walk: The Adaptive Suspension Vehicle
Optimal turning gait of a six-legged robot using a GA-fuzzy approach

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Robotics and Computer-Integrated Manufacturing
Effects of turning gait parameters on energy consumption and stability of a six-legged walking robot

Robotics and Autonomous Systems

Dynamic modeling, stability and energy consumption analysis of a realistic six-legged walking robot

Robotics and Computer-Integrated Manufacturing
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Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Recent Advances in Soft Computing: Theories and Applications

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Abstract

Turning gaits are the most general and very important ones for omni-directional walking of a six-legged robot. Soft computing-based expert systems have been developed in the present work to predict specific energy consumption and stability margin of turning gait of a six-legged robot. Besides back-propagation neural network, three approaches based on adaptive neuro-fuzzy inference system have been developed and their performances are compared with each other. Genetic algorithm-tuned multiple adaptive neuro-fuzzy inference systems are found to perform better than other approaches. This could be due to a more exhaustive search conducted by the genetic algorithm in place of back-propagation algorithm and the use of two separate adaptive neuro-fuzzy inference systems for two different outputs.