The field of robotics is moving towards more dexterous and autonomous manipulation capabilities, with a focus on developing innovative control systems and mechanisms that can handle complex tasks with precision and accuracy. Researchers are exploring new designs and control strategies for robotic hands, fingers, and arms, as well as advancing the field of haptic feedback and force sensing. Noteworthy papers in this area include the development of a mechanically isomorphic exoskeleton data collection system, a modular force feedback glove, and a framework for learning dexterous manipulation skills from imperfect simulations. These advancements have significant implications for applications such as robotic assembly, surgery, and human-robot collaboration.
Notable papers: MILE introduces a mechanically isomorphic exoskeleton data collection system for dexterous manipulation. KinesCeTI presents a modular force feedback glove with interchangeable actuation for the index and thumb. Learning Dexterous Manipulation Skills from Imperfect Simulations proposes a framework for learning manipulation skills from simplified simulations.
