Locomotion of Hybrid Mechanical Systems with Impacts
F. Bullo,* M. Zefran*
University of Illinois; National Science Foundation, CMS-9502224

An area of increasing interest is modeling and control of hybrid mechanical systems, that is, locomotion and grasping devices that interact with the environment via contacts and collisions. Examples are hopping and walking robots, robots that progress by swinging arms, and devices that switch between clamped, sliding, and rolling regimes Within this context, the engineering goal is to analyze and design systems that accomplish various tasks efficiently and robustly. This motivation leads to a number of problems that arise in the interaction of discontinuities, locomotion, and stability. From a broader perspective, these challenges are independent interests because they highlight connections between the fields of robotics, hybrid systems, and control theory.

Adaptive Control of Underactuated Mechanical Systems
M. W. Spong*
National Science Foundation, CMS 9402229

This project concerns the nonlinear control of underactuated mechanical systems. This class of systems is quite broad and encompasses flexible structures of all kinds including flexible link robots, flexible joint robots, as well as robot models that include actuator dynamics, and many of the classical control problems like the ball-and-beam and cart-pole systems. Techniques such as partial feedback linearization, singular perturbations, and passivity methods are being applied for global and semiglobal stabilization of these systems.

Development of an Air Hockey Playing Robot
M. W. Spong,* S. Hutchinson (Elect. & Comput. Engr.), B. Bishop, C. Partridge
National Science Foundation, IRI-9216428, CMS-9712170; Electric Power Research Institute, RP 8030-14

This project is to develop a three-degree-of-freedom air hockey playing robot. Research issues being addressed include real-time visual serving, adaptive camera calibration and windowing, hybrid estimation, and hybrid nonlinear control. Based on the reliability of sensory information, a supervisory control system switches among a fixed set of nonlinear controllers, each designed for a particular task such as blocking or striking the puck. Future research is aimed at learning through repetitive play.

Integration of Machine Learning and Sensor-based Control in Intelligent Robotic Systems
M. W. Spong,* J. DeJong (Comput. Sci.), S. Hutchinson (Elect. & Comput. Engr.), B. Bishop
National Science Foundation, IRI 92-16428; Electric Power Research Institute, RP 8030-14

This project concerns the integration of machine learning and sensor-based control in intelligent robotic systems. The research combines techniques of explanation-based control with robust and adaptive nonlinear control, computer vision, and robot motion planning. We wish to go beyond the strict hierarchical control architectures typically used in robotic systems by integrating modeling, dynamics, and control at all levels of intelligence. Our ultimate goal is to combine analytical techniques of nonlinear dynamics and control with artificial intelligence into a single new paradigm, in which symbolic reasoning holds an equal place with differential equation-based modeling and control.

Learning Sensorimotor Control of Balance and Locomotion
M. W. Spong,* K. Rosengren, S. Hutchinson (Elect. & Comput. Engr.), R. Sreenivas, J. DeJong (Comput. Sci.)
National Science Foundation, ECS-9812591

This project investigates the modeling of the sensorimotor control systems in humans and robots. We use techniques from control theory and artificial intelligence to understand dynamics and control of human motion and the mechanisms by which humans learn sensorimotor control. At the same time, we use studies of human motion to aid the development of improved control techniques for mechanical systems. Future applications of our work will include more dextrous robots and more effective diagnostics and physical therapy approaches for disabled humans, as well as better balance training and fall-prevention programs for elderly and individuals with balance deficits.

Nonlinear Control of Underactuated Mechanical Systems
M. W. Spong*
National Science Foundation, CMS-9712170, CMS-9840985

This project seeks to develop stability and tracking results for underactuated mechanical systems using tools from Lagrangian and Hamiltonian dynamics, geometric nonlinear control theory, hybrid control, and saturation. Our work exploits the underlying structure of the nonlinear existing energy and passivity methods and more recent backstepping methods, all of which attempt to exploit more fully the inherent nonlinearities of the system, by "shaping" rather than by "canceling" all of the nonlinearities in the system.