The ability to avoid collisions is crucial for locomotion in cluttered environments. It is not enough to plan collision-free movements in advance when the environment is dynamic and not precisely known. We developed a new method which generates locally optimized trajectories online during the feedback control in order to dynamically avoid obstacles. This method successfully combines a local potential field method with a heuristic based on height and width of an obstacle to avoid collisions. The program's main feature is the integration of obstacles into the framework designed for self-collision avoidance presented in [1] and the collisions avoidance in task-space. We show experimental results validating the method.
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Hildebrandt et al. (2014) studied this question.
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