NRI: FND: COLLAB: Hierarchical Safe, and Distributed Feedback Control of Multiagent Legged Robots for Cooperative Locomotion and Manipulation

Virginia Polytechnic Institute And State University, Blacksburg VA

Investigators

Abstract

The project aims to realize legged co-robots that cooperatively work with each other or people to achieve a variety of tasks in complex environments. One of the most challenging problems in deploying the next generation of ubiquitous co-robots is mobility in complex environments. More than half of the Earth's landmass is inaccessible to wheeled vehicles this motivates utilizing legged co-robots to access these environments and thus bring robots into the real world. Legged robots that are augmented with manipulators can form co-robot teams that assist humans in different aspects of their life. Although important theoretical and technological advances have enabled the development of distributed controllers for complex robot systems, including multiagent systems composed of collaborative robotic arms, multifingered robot hands, aerial vehicles, and ground vehicles, understanding how to control cooperative legged agents is an open problem. The challenges in achieving coordination in this domain stems from the fact that legged robots are inherently unstable, and the evolution of legged co-robot teams is represented by high-dimensional and complex hybrid dynamical systems which complicate the design of distributed control algorithms for control and coordination. There is a fundamental gap in knowledge of distributed control algorithms for safety-critical control of these inherently unstable, underactuated, and complex hybrid dynamical systems. The overarching goal of this proposal is to create a formal foundation, based on hybrid systems theory, scalable optimization, and robust and safety-critical control, to develop distributed and hierarchical feedback control algorithms for cooperative legged co-robots with manipulators to achieve a variety of tasks in complex environments. The proposed research will have broad societal impact through the formally principled and safety-critical deployment of ubiquitous collaborative legged robots in scenarios where robots can assist humans, e.g., disaster response. The integrated educational plan will have broad impact by designing a new course based upon the results, utilizing robots for STEM-based outreach for K-12 students, teachers, and under-represented minorities. The project aims to develop resilient and versatile algorithms that address cooperative locomotion and manipulation of high-dimensional hybrid models of legged co-robot teams in a safe, stable, and reliable manner. These algorithms will further enable legged co-robot teams to adapt to new tasks and environments with minimal modification to software. It will advance knowledge in the largely unexplored field of distributed control of large-scale hybrid system models of legged co-robots through specific objectives and key innovations in Scalability and Customizability. Intelligent and optimization-based motion planning algorithms will be created for hybrid models of legged co-robots to adapt to a wide variety of complex environments and new situations. Distributed and hierarchical control algorithms, based on nonlinear, robust and predictive controllers, together with scalable convex optimization, will be developed for coordination of multiagent legged robotic systems to enable agile locomotion patterns while manipulating objects in a dexterous manner. Finally, safety-critical control methods, based on set invariance and convex optimization, will be integrated with the hierarchical and distributed controllers for obstacle avoidance. To bridge the gap between theory and implementation, the proposed research will transfer the theoretical innovations into practice through experiments with a co-robot team consisting of multiple quadruped robots and one humanoid robot working collaboratively. 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.