2 papers
cs.RO2026
CAST: Alternating State-Value Targets and Expanded Policy Gradients for Model-Based Reinforcement Learning
Pietro Noah Crestaz, Mohamed Yassine Kabouri, Nicolas Mansard +1
Model-based reinforcement learning (MBRL) is a family of RL methods that learn a model of the environment and use it for action selection, making it well suited to robotics due to…
cs.RO2026
Embodied Active Learning under Limited Annotation and Navigation Budget for Object Detection
Hadrien Crassous, Mohamed Yassine Kabouri, Minahil Raza +2
This paper studies how to adapt a computer vision object detector to an unknown environment under both a robot navigation time and annotation budget constraint. Our approach select…