273 citations · 633 across the 38 of their papers we have counts for
3 papers · 2 filters
MEM: Multi-Scale Embodied Memory for Vision Language Action Models
Marcel Torne, Karl Pertsch, Homer Walke +14
Conventionally, memory in end-to-end robotic learning involves inputting a sequence of past observations into the learned policy. However, in complex multi-stage real-world tasks,…
Steerable Vision-Language-Action Policies for Embodied Reasoning and Hierarchical Control
William Chen, Jagdeep Singh Bhatia, Catherine Glossop +6
Pretrained vision-language models (VLMs) can make semantic and visual inferences across diverse settings, providing valuable common-sense priors for robotic control. However, effec…
RoboReward: General-Purpose Vision-Language Reward Models for Robotics
Tony Lee, Andrew Wagenmaker, Karl Pertsch +3
A well-designed reward is critical for effective reinforcement learning-based policy improvement. In real-world robotics, obtaining such rewards typically requires either labor-int…