activity
20202026
most citedLearning Context-Adaptive Task Constraints for Robotic Manipulation

9 citations · 15 across the 11 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

cs.RO2025

InEKFormer: A Hybrid State Estimator for Humanoid Robots

Lasse Hohmeyer, Mihaela Popescu, Ivan Bergonzani +2

Humanoid robots have great potential for a wide range of applications, including industrial and domestic use, healthcare, and search and rescue missions. However, bipedal locomotio…

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

Parallel Transmission Aware Co-Design: Enhancing Manipulator Performance Through Actuation-Space Optimization

Rohit Kumar, Melya Boukheddimi, Dennis Mronga +2

In robotics, structural design and behavior optimization have long been considered separate processes, resulting in the development of systems with limited capabilities. Recently,…

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…

cs.RO2025★ 1 cited

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…