Nuria Armengol Urpí

CAIMAN: Causal Action Influence Detection for Sample-Efficient Loco-Manipulation

Enabling legged robots to perform non-prehensile loco-manipulation is crucial for enhancing their versatility. However, learning behaviors such as whole-body object pushing often necessitates sophisticated planning strategies or extensive task-specific reward shaping. In this work, we present CAIMAN…