| सारांश: | Different legged robot locomotion controllers have different advantages and disadvantages, from speed of motion to energy, computational speed, safety and others. In this paper we propose a method for planning locomotion with multiple controllers and sub-planners, explicitly considering the multiobjective nature of the problem. We propose a parameter-free method that plans in the space of body motion and controller choice, using utopian and lexicographic cost aggregation functions. We empirically analyze the behavior of the method in terms of planning success rates, Pareto-optimality and anytime behavior in cost space. We show that our method is faster than pure footstep planning methods both in computation (2x) and mission time (1.4x), it is safer than pure dynamic-walking methods, and achieves desirable Pareto-optimal solutions (up to 8x) faster than fairly-tuned traditional weighted-sum methods. Our conclusions are drawn from a combination of planning, physics simulation, and real robot experiments.
|
|---|