Retraction Maps, Feedback Linearization and Nonholonomic Integrators Ravi Banavar, Professor, Systems and Control Engineering, IIT Bombay May 1, 12:00 - 13:00 B9 L2 R2325 This talk will introduce the utility of retraction maps on Riemannian manifolds to two applications in applied mechanics and control.
Feedback system design for tuning cooperative behavior in multi-agent games Shinkyu Park, Assistant Professor, Electrical and Computer Engineering Apr 24, 12:00 - 13:00 B9 L2 R2322 H1 Feedback system design In social dilemmas, a class of multi-agent games, agents' rationality-based strategic interactions to learn a payoff-maximizing strategy would result in diminishing returns. Such games include the prisoner's dilemma and public goods game where individually rational decision making reults in all decision-making agents receiving smallest rewards. In this presentation, I will explain a new decision-making model that elicits cooperative behavior in social dilemmas. The model enables the social interaction (reciprocity) between agents in their decision making, which allows cooperative behavior to emerge. We discuss how methods for feedback system design and analysis can be applied to explain the emergence of cooperative behavior and how we can tune such behavior.
The KAUST Research Conference on Robotics and Autonomy 2022 Eric Feron, Professor, Electrical and Computer Engineering Feb 28, 08:00 - Mar 2, 20:00 B19 H1 robotics KAUST Robotics, Intelligent Systems and Control Lab (RISC Lab) will host the KAUST Research Conference on Robotics and Autonomy 2022 (#RobotoKAUST) from February 28 until March 2, 2022. The conference will address the most recent trends of robotics application in a range of disciplines. To attend RobotoKAUST Gala, please, read more about the event and follow the event registration instructions.
Social Decision Making for Robot Navigation Shinkyu Park, Assistant Professor, Electrical and Computer Engineering Oct 31, 12:00 - 13:00 KAUST Social robot navigation Robot navigation typically comprises of decision making at two different levels - global planning to compute a viable trajectory to the robot's destination and strategic (local) interaction to elicit cooperation and resolve any conflicts with other robots/pedestrians that would arise while navigating along the trajectory. Robot navigation in crowded environments is particularly challenging as the robot needs to exhibit navigation behaviors that are conceived as socially compliant by human pedestrians or vehicles they maneuver at both of the levels. In this presentation, I will introduce some of relevant works from my research group.
