6 accepted papers
Searching for effective policies in high-dimensional action spaces is notoriously challenging. This difficulty is compounded in overactuated musculoskeletal systems, where multiple muscles span each joint, and individual muscles actuate multiple joints. Although this redundancy complicates naive pol…
Recent advancements in bionic prosthetic technology offer transformative opportunities to restore mobility and functionality for individuals with missing limbs. Users of bionic limbs, or bionic humans, learn to seamlessly integrate prosthetic extensions into their motor repertoire, regaining critica…
Human dexterity is a hallmark of motor control behaviors. Our hands can rapidly synthesize new behaviors despite the complexity (multi-articular and multi-joints, with 23 joints controlled by more than 40 muscles) of mosculoskeletal control. In this work, we take inspiration from how human dexterity…
We present RoboHive, a comprehensive software platform and ecosystem for research in the field of Robot Learning and Embodied Artificial Intelligence. Our platform encompasses a diverse range of pre-existing and novel environments, including dexterous manipulation with the Shadow Hand, whole-arm man…
Learning effective continuous control policies in high-dimensional systems, including musculoskeletal agents, remains a significant challenge. Over the course of biological evolution, organisms have developed robust mechanisms for overcoming this complexity to learn highly sophisticated strategies f…
Owing to the restrictions of live experimentation, musculoskeletal simulation models play a key role in biological motor control studies and investigations. Successful results of which are then tried on live subjects to develop treatments as well as robot aided rehabilitation procedures for addressi…