Dexterous Manipulation and Language-Conditioned Robotics
Robotic manipulation is a complex challenge, requiring precision, dexterity, and adaptability to handle the vast variety of objects humans interact with daily. While humans naturally develop these skills over time, teaching robots to replicate this level of finesse remains difficult. My research explores advanced manipulation strategies, focusing on dexterous and bimanual control, to enable robots to interact more fluidly with their environments. These capabilities are key for real-world applications, where robots must handle both delicate and complex tasks in human-centric environments.
However, manipulation alone is not enough. Effective human-robot interaction requires intuitive communication, and language plays a pivotal role in bridging that gap. By integrating language understanding with robot control, my work empowers robots to interpret human instructions and adapt their manipulation strategies accordingly. This combination allows for more natural, human-like interactions, where robots not only manipulate objects skillfully but do so in response to nuanced verbal commands. Together, these advancements are driving the development of next-generation assistive robots capable of seamlessly interacting with both their environment and the people in it.