Gait Planning of Biped Robots Using Soft Computing: An Attempt to Incorporate Intelligence

This chapter deals with the issues related to incorporation of intelligence using soft computing to biped robots moving on some uneven terrains, such as staircases, sloping surfaces, ditches, and others. The said problems have been solved utilizing both analytical as well as soft computing-based approaches. In the analytical approach, the concepts of inverse kinematics and static balance have been used to generate the gaits of lower limbs and trunk, respectively, and its dynamic balance has been verified utilizing the position of zero moment point, whereas in soft computing-based approaches, either neural network- or fuzzy logic-based gait planner has been used to generate the motion of trunk and swing foot of the biped robot. The knowledge bases of neural network and fuzzy logic-based approaches have been optimized separately using a genetic algorithm off-line. The performances of the developed approaches have been tested through computer simulations.

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