QuadPiPS combines semantic affordance prediction with an egocentric legged egocan representation and trajectory optimization to produce kinodynamically feasible foothold plans that outperform baselines in limited-foothold settings and run on hardware.
Heterogeneous robot teams with uni- fied perception and autonomy: How Team CSIRO Data61 tied for the top score at the DARPA Subterranean Challenge
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QuadPiPS: A Perception-informed Footstep Planner for Quadrupeds With Semantic Affordance Prediction
QuadPiPS combines semantic affordance prediction with an egocentric legged egocan representation and trajectory optimization to produce kinodynamically feasible foothold plans that outperform baselines in limited-foothold settings and run on hardware.