Research Projects
Theory of Mind
A cornerstone of human-human interaction is our ability to infer our partner’s beliefs, desires, and intentions, allowing us to effectively collaborate with each other towards a common goal. The capacity to formulate such a mental model is known as theory of mind. As we seek to impart similar capabilities to embodied agents when interacting with humans, there is a need to develop methods that tackle both sides of the interaction: 1) theory of mind in which a mental model of the human is held by the agent, and 2) theory of machine in which a mental model of the agent is held by the human. While this mental modeling is important in all types of human-agent teaming, this is especially so in the context of heterogeneous teams in which embodied agents with fundamentally different capabilities collaborate with humans.
Language Conditioned Imitation Learning
Our ability to utilize language plays a critical role in our daily lives by allowing us to efficiently communicate our thoughts to build a mutual understanding. Studying language in robotics is a key to understanding how intelligence works and will allow us to build next-generation assistive robots that can intuitively and effectively interact with humans. To this end, my research focuses on integrating language understanding with robot control by bridging the gap between cognition and robotics, utilizing modern approaches to artificial intelligence and robotics.
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.
