VoxAct-B: Voxel-Based Acting and Stabilizing Policy for Bimanual Manipulation

By I-Chun Arthur Liu Bimanual manipulation is essential for robots to manipulate objects as well as humans. It becomes necessary when objects are too large to be controlled by one hand or when using one hand to stabilize an object makes it easier for the other hand to manipulate it. In this work, we focus … Continue reading VoxAct-B: Voxel-Based Acting and Stabilizing Policy for Bimanual Manipulation

ViSaRL: Saliency-Guided Visual Representations for Robot Learning

By Anthony Liang Teaching robots to perform complex control tasks from high-dimensional image inputs is a nontrivial problem. State-of-the-art methods require hundreds of manually collected expert demonstrations or hours to days of training in simulation to learn a simple pick-and-place skill. One reason for this is that images are cluttered with distractions for robots, such … Continue reading ViSaRL: Saliency-Guided Visual Representations for Robot Learning

Language Models meet Classical Planners to make smarter Robot Task Plans

By Ishika Singh Everyday household tasks require both common sense understanding of the world and situated knowledge about the current environment. To create a task plan for “Make dinner” an agent needs common sense: object affordances, such as the stove can be used to make food; logical sequences of actions, such as the oven must be preheated … Continue reading Language Models meet Classical Planners to make smarter Robot Task Plans