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Harold delivers ICRA'24 Keynote

Harold gave a well-received Keynote at ICRA’24 on our group’s work on generative modeling and robotics! He spoke about two of our recent works on new kinds o...

Octopi: Object Property Reasoning with Large Tactile-Language Models

We introduce PhysiCLeaR, an annotated dataset of everyday objects and tactile readings collected from a Gelsight Mini sensor, as well as Octopi, a system that leverages both tactile representation learning and large vision-language models to perform physical reasoning and inference, given tactile videos of multiple objects.

4 Papers at R:SS'24.

All four of our submissions (3 papers, 1 demo) were accepted to R:SS 2024! A fantastic accomplishment by our CLeAR members Kaiqi, Samson, Tasbolat, Linh, Kel...

Don’t Start from Scratch: Behavioral Refinement via Interpolant-based Policy Diffusion

We develop interpolant policies that diffuse actions from informative source distributions.

GRaCE: Balancing Multiple Criteria to Achieve Stable, Collision-Free, and Functional Grasps

We propose an optimization-based grasp synthesis framework, GRaCE, to generate context-specific grasps in complex scenarios. We test GRaCE in a simulator and a real-world grasping tasks.

Probable Object Location (POLo) Score Estimation for Efficient Object Goal Navigation

We introduce a novel framework centered around the Probable Object Location (POLo) score, which allows the agent to make data-driven decisions for efficient object search.

Selective Amnesia: A Continual Learning Approach to Forgetting in Deep Generative Models

We apply techniques from continual learning to the problem of selective forgetting in deep generative models. Our method, dubbed Selective Amnesia, allows users to remap undesired concepts to user-defined ones.