From the 1 of 27 linked papers with an AI index.
14 papers · 1 filter
PAINT: Partner-Agnostic Intent-Aware Cooperative Transport with Legged Robots
Zhihao Cao, Tianxu An, Chenhao Li +2
Collaborative transport requires robots to infer partner intent through physical interaction while maintaining stable loco-manipulation. This becomes particularly challenging in co…
CAIMAN: Causal Action Influence Detection for Sample-efficient Loco-manipulation
Yuanchen Yuan, Jin Cheng, Núria Armengol Urpà +1
Enabling legged robots to perform non-prehensile loco-manipulation is crucial for enhancing their versatility. Learning behaviors such as whole-body object pushing often requires s…
What Matters for Simulation to Online Reinforcement Learning on Real Robots
Yarden As, Dhruva Tirumala, René Zurbrügg +4
We investigate what specific design choices enable successful online reinforcement learning (RL) on physical robots. Across 100 real-world training runs on three distinct robotic p…
Problem Space Transformations for Out-of-Distribution Generalisation in Behavioural Cloning
Kiran Doshi, Marco Bagatella, Stelian Coros
The combination of behavioural cloning and neural networks has driven significant progress in robotic manipulation. As these algorithms may require a large number of demonstrations…
TARC: Time-Adaptive Robotic Control
Arnav Sukhija, Lenart Treven, Jin Cheng +3
Fixed-frequency control in robotics imposes a trade-off between the efficiency of low-frequency control and the robustness of high-frequency control, a limitation not seen in adapt…
SPiDR: A Simple Approach for Zero-Shot Safety in Sim-to-Real Transfer
Yarden As, Chengrui Qu, Benjamin Unger +6
Deploying reinforcement learning (RL) safely in the real world is challenging, as policies trained in simulators must face the inevitable sim-to-real gap. Robust safe RL techniques…