Robot Manipulation

Throughout our lifetime, we learn to delicately grasp, manipulate, and use a wide range of objects, allowing us to use these abilities to interact with the world and other people in it. The acquired experience then enables us to learn complex interactions with our environment, such as increased dexterity in object manipulation and compliant manipulation of complex objects. However, we also shape the world around us to make interactions more accessible and more intuitive for the human physique. In this project, I am bridging the gap between robot capabilities and manipulation affordances in the real world by investigating dexterous and bimanual manipulation strategies using novel approaches in artificial intelligence and control.

• Video

  A System for Imitation Learning of Contact-Rich Bimanual Manipulation Policies
• Video

  Contact-Rich Bimanual Manipulation
• News

  Our paper in collaboration with Intrinsic got accepted to IROS 2022, which we will be presenting in Kyoto, Japan. View full paper

• Publication

  A System for Imitation Learning of Contact-Rich Bimanual Manipulation Policies
• Publication

  Language-Conditioned Human-Agent Teaming
• News

  Over the summer, I will be a resident at X, The Moonshot Factory, where I will be working on industrial manipulation tasks for Intrinsic, a robotics software and AI project at X .

• Publication

  Language-Conditioned Imitation Learning for Robot Manipulation Tasks
• Publication

  Imitation Learning of Robot Policies by Combining Language, Vision, and Demonstration
• Publication

  Extrinsic Dexterity Through Active Slip Control Using Deep Predictive Models
• News

  We got our paper accepted to ICRA 2018, and I will be presenting our work in Brisbane, Australia! Paper on IEEE Xplore

• Projects

  Robot Manipulation
• Publication

  Active Slip Control for In-Hand Object Manipulation using Deep Predictive Models
• Publication

  Deep Predictive Models for Active Slip Control

manipulation