5 accepted papers
In this letter, we investigate whether classical function allocation—the principle of assigning tasks to either a human or a machine—holds for physical Human-Robot Collaboration, which is important for providing insights for Industry 5.0 to guide how to best augment rather than replace workers. This
Skill propagation among robots without human involvement can be crucial in quickly spreading new physical skills to many robots. In this respect, it is a good alternative to pure reinforcement learning, which can be time-consuming, or learning from human demonstration, which requires human involveme
In this work, we explore using computational musculoskeletal modeling to equip an industrial collaborative robot with awareness of the internal state of a patient to safely deliver physical therapy. A major concern of robot-mediated physical therapy is that robots may unwittingly injure patients. Fo
Much of ongoing robotic endoscope research is focused on locomotion, with only limited exploration into feedback control and autonomy in the unconventional and dynamic in vivo environment. This letter presents a modular endoscopy simulation apparatus (MESA) to quickly, affordably, and repeatedly tes
While in vivo robotic locomotion has demonstrated its potential through a number of means, sensing and closed-loop control for such devices have not been at the forefront of research. By enabling real-time navigation, capsule endoscopy could transform from passive capsule endoscopes (CEs) and remote