The project aims to give legged robots the skills to navigate a wide variety of terrain. This capability is needed to employ robots in applications such as search-and-rescue, construction, and exploration of remote environments on Earth and other planets. The multidisciplinary team, composed of researchers at Duke, Stanford, UC Santa Barbara, JPL, and Motiv Robotics, will develop a robot to climb a variety of surfaces ranging from flat ground to overhanging cliffs. Using an array of sensors, unique hands, and sophisticated algorithms, the robot will dynamically adopt walking, crawling, climbing, and swinging strategies to traverse wildly varied terrain. During the course of this research, the team hopes to achieve the milestone of the first demonstration of a human-scale rock climbing robot. The research is also expected to lead to insights into cognitive and biomechanical processes in human and animal locomotion.
Although rock climbing serves as an ideal proving ground for the work, this project conducts basic research to address more a general-purpose goal; namely, to provide the physical and cognitive skills for robots to adaptively navigate varied terrain. It takes a dexterous climbing approach, which uses non-gaited, coordinated sequences of contact to move the body, much as dexterous manipulation uses contact with the fingers and palm to move an object. It will apply principles from optimization, machine learning, bioinspiration, and control theory to make intellectual contributions in several domains, such as robot hand design, planning algorithms, balance strategies, and locomotion performance measurement. Novel grippers, sensor-based planning strategies, reactive maneuvers, and locomotion metrics will be developed during the course of this research.
