This Faculty Early Career Development (CAREER) project will focus on creating new methods to model, estimate, and control the movement of legged robots for enabling stable locomotion on dynamic rigid surfaces (DRS) (i.e., surfaces that move and do not deform). While today’s legged robot systems have demonstrated remarkable capabilities in traversing stationary surfaces (e.g., stairs, sand, and grass), legged locomotion on DRS (e.g., ships, aircraft, and trains) is a new robot functionality that has not been addressed. This new functionality will empower legged robots to negotiate complex, dynamic human environments (that are prohibitively challenging for wheeled or tracked robots) to allow them to aid in numerous critical high-risk applications, such as shipboard firefighting and fire suppression and cleaning/disinfection of public transportation vehicles to contain the spread of infectious diseases. Enabling such functionality demands reliable robot estimation and control, which are substantially challenging due to the high complexity of the associated robot behaviors that are hybrid (involving continuous leg-swinging motions and discrete foot-landing events) and subject to the time-varying DRS movement. The CAREER research program seeks to solve these fundamental problems and lay a foundation for the development of next-generation legged robot systems capable of autonomous navigation on nonstationary surfaces. The CAREER education program will enhance the robotics curriculum at the University of Massachusetts Lowell while engaging diverse groups, including underrepresented undergraduate and graduate students, K-12 students, and the general public, in robotics education and research.
The research goal of the project is to draw upon dynamic modeling, state estimation, feedback control, and theory of hybrid systems to advance the control theory of legged robots in order to realize provably stable legged locomotion on a DRS. To achieve the research goal, four main objectives will be pursued: (i) formulation of a physics-based model that captures the hybrid, time-varying robot dynamics associated with legged locomotion on a DRS; (ii) creation of new methods of designing state estimators that achieve real-time state estimation with convergence guarantees by provably expanding an invariant filtering methodology from continuous systems to hybrid dynamical systems that include legged robots moving on a DRS; (iii) derivation of a Lyapunov-based controller design methodology to produce stable locomotion on a DRS by handling the hybrid, time-varying robot dynamics under uncertainties that reside in both continuous phases and discrete events; and (iv) integration of the modeling, state estimation, and controller design into a model-based framework that provably sustains legged locomotion on a DRS. The project will support the PI to solve major robotics challenges beyond the capabilities of the state of the art, and help establish a long-term career in robotics and control.
This project is supported by the cross-directorate Foundational Research in Robotics program, jointly managed and funded by the Directorates for Engineering (ENG) and Computer and Information Science and Engineering (CISE).
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
