Control of walking appears as a complex problem. Many solutions use pre-defined gait pattern or tactile information for gait adaptation. This strategy has some limitations for adaptation in complex terrain. Gait planning promises more success in difficult terrain. In this approach, a planning algorithm based on random sampling is introduced. Terrain information is provided by the introduced stereo vision algorithm. Both algorithms are designed to work in real-time. Experimental and simulational results have shown that the algorithma are generally applicable for motion planning of legged vehicles.
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