Why cannot the current robots act intelligently in the real-world environment? A major challenge lies in the lack of adequate tactile sensing technologies. Robots need tactile sensing to understand the physical environment, and detect the contact states during manipulation. Progress requires advances in the sensing hardware, but also advances in the software that can exploit the tactile signals. We developed a high-resolution tactile sensor, GelSight, which measures the geometry and traction field of the contact surface. For interpreting the high-resolution tactile signal, we utilize both traditional statistical models and deep neural networks.
I will describe my research on both exploration and manipulation. For exploration, I use active touch to estimate the physical properties of the objects. The work has included learning the hardness of artificial objects, as well as estimating the general properties of natural objects via autonomous tactile exploration. For manipulation, I study the robot’s ability to detect slip or incipient slip with tactile sensing during grasping. The research helps robots to better understand and flexibly interact with the physical world.
Biography: Wenzhen Yuan is a Ph.D. candidate in the Department of Mechanical Engineering at MIT, affiliated with Computer Science and Artificial Intelligence Laboratory (CSAIL). Her dissertation research is supervised by Prof. Edward Adelson and Dr. Mandayam Srinivasan. Her research interests include robotic tactile sensing, as well as robotic perception in other modalities. She received her Master of Science degree from MIT, and Bachelor of Engineering degree from Tsinghua University.