Dynamic Grasp Adaptation

The human hand is an amazing tool, demonstrated by its incredible motor capability and remarkable sense of touch. To enable robots to work in a human-centric environment, it is desirable to endow robotic hands with human-like capabilities for grasping and object manipulation. However, due to its inherent complexity and inevitable model uncertainty, robotic grasping and manipulation remains a challenge. This book focuses on grasp adaptation in the face of model and sensing uncertainties: Given an object whose properties are not known with certainty (e.g., shape, weight and external perturbation), and a multifingered robotic hand, we aim at determining where to put the fingers and how the fingers should adaptively interact with the object using tactile sensing, in order to achieve either a stable grasp or a desired dynamic behaviour.

Autorentext

Miao Li is an associate professor at Wuhan University China who obtained his PhD from EPFL, Switzerland. His research interests are in robotics, machine learning and applied nonlinear control. They encompass robot learning and control, object grasping and manipulation, human-robot interaction, robotic hand and tactile sensing, and neuroscience.