4 accepted papers
In real-world settings, bipedal robots must avoid collisions with people and their environment. Further, a biped can choose between modes of avoidance: (1) adjust its pose while standing or (2) step to gain maneuverability. We present a real-time motion planner and multibody control framework for dy…
We present a real-time motion planner that avoids multiple moving obstacles without knowing their dynamics or intentions. This method uses convex optimization to generate trajectories for linear plant models over a planning horizon (i.e. model-predictive control). While convex optimizations allow fo…
Tracks, wheels, and legs are all useful locomotion modes for Unmanned Ground Vehicles (UGVs), and ground robots that combine these mechanisms have the potential to climb over large obstacles. As robot morphologies include more degrees of freedom and obstacles become increasingly large and complex, U…
Out in the field, bipedal robots need to travel on terrain that is uneven, non-rigid, and sometimes moving beneath their feet. We present a force-based double support balancing controller for such dynamic terrain scenarios for bipedal robots, and test it on the robotic bipedal platform "Tallahassee…