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Quadrupeds for Planetary Exploration: Field Testing Control Algorithms on an Active Volcano
Shubham Vyas, Franek Stark, Rohit Kumar +6
Missions such as the Ingenuity helicopter have shown the advantages of using novel locomotion modes to increase the scientific return of planetary exploration missions. Legged robo…
An adaptive hierarchical control framework for quadrupedal robots in planetary exploration
Franek Stark, Rohit Kumar, Shubham Vyas +6
Planetary exploration missions require robots capable of navigating extreme and unknown environments. While wheeled rovers have dominated past missions, their mobility is limited t…
Adaptive Model-Base Control of Quadrupeds via Online System Identification using Kalman Filter
Jonas Haack, Franek Stark, Shubham Vyas +2
Many real-world applications require legged robots to be able to carry variable payloads. Model-based controllers such as model predictive control (MPC) have become the de facto st…
Reinforcement Learning for Robust Athletic Intelligence: Lessons from the 2nd 'AI Olympics with RealAIGym' Competition
Felix Wiebe, Niccolò Turcato, Alberto Dalla Libera +17
In the field of robotics many different approaches ranging from classical planning over optimal control to reinforcement learning (RL) are developed and borrowed from other fields…
Benchmarking Different QP Formulations and Solvers for Dynamic Quadrupedal Walking
Franek Stark, Jakob Middelberg, Dennis Mronga +2
Quadratic Programs (QPs) are widely used in the control of walking robots, especially in Model Predictive Control (MPC) and Whole-Body Control (WBC). In both cases, the controller…