Natural selection has enabled us to adapt to our environments and achieve complex tasks with relative ease, especially in the area of legged locomotion. These abilities have not yet been translated to bipedal robots, despite the use of complex models, computing power, and novel actuators and sensors. This gap between simulated and observed behavior gets wider with more dynamic tasks like running. Therefore, this talk focuses on a mathematical framework that formalizes the process of implementation in real world systems, i.e., that bridges the divide between theory and experiment. Specifically, the notion of input-to-state stability (ISS) is applied for the construction of robust controllers for a class of hybrid systems that characterize bipedal robots. By treating uncertainties (modeling, model parameter, measurement), or functions of uncertainties as inputs to a system, the talk will describe how to reduce this to a form amenable for input-to-state stability analysis. With this analysis, robust controllers are realized, with the goal of realizing dynamic locomotion behaviors like walking and running, thereby bridging the gap between theory and experiment. This will be demonstrated on multiple robotic platforms including a humanoid robot and running robot.
Shishir is a Postdoctoral scholar working for AMBER Lab in the California Institute of Technology. He received his PhD degree in Mechanical Engineering (2016) from the Georgia Institute of Technology, M.S. degree in Electrical Engineering (2012) from Texas A & M University, and B. Tech degree in Electrical & Electronics Engineering (2008) from the National Institute of Technology Karnataka, Surathkal, India. Prior to pursuing his Master's degree, he also worked for two years as a power supply designer in Tejas Networks Ltd., Bangalore. Shishir has been an integral part of AMBER Lab for more than six years working with Dr. Aaron Ames across three different institutions from 2011-2017. He is interested in nonlinear control, dynamical systems, hybrid dynamical systems, robotics, and particularly in bipedal locomotion.