collaborators

7 papers

cs.RO2026

Right Model, Right Time: Real-Time Cascaded-Fidelity MPC for Bipedal Walking

Franek Stark, Felix Wiebe, Shubham Vyas +2

This paper presents a multi-phase whole-body model predictive control (MPC) approach for bipedal walking, combining a detailed whole-body model in the near horizon with a simplifie…

eess.SY2026

Mixed-Integer vs. Continuous Model Predictive Control for Binary Thrusters: A Comparative Study

Franek Stark, Jakob Middelberg, Shubham Vyas

Binary on/off thrusters are commonly used for spacecraft attitude and position control during proximity operations. However, their discrete nature poses challenges for conventional…

cs.RO2025

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…

cs.RO2025

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…

cs.RO2025

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…

cs.RO2025

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…