Inaugural Lecture: Prof. Sethu Vijayakumar

2012 is the year of the London Olympics and, appropriately, this talk is about making robots run faster, jump higher and throw further while being as versatile, robust and adaptive as humans. We are very adept at performing fast, complicated control tasks, even in the face of sensorimotor delays, noise and perturbations -- think of the dexterity of a surgeon or even the simple task of crossing a road without getting run over. Matching this with autonomous robotics systems is challenging. Broadly speaking, challenges lie in the domain of robust sensing, flexible planning, appropriate representation and adaptive dynamics under various contexts. Statistical Machine Learning provides ideal tools to deal with these challenges, especially in tackling issues like partial observability, noise, redundancy resolution and scalability. I will illustrate some of our success stories and talk about the spills and thrills of working on exciting robotics platforms such as KUKA and SARCOS dexterous arms, Touch Bionics iLIMB and humanoid robots such as the HONDA ASIMO, DB and the Nao footballers. I will also reflect on the impact of this work on domains ranging from assisted living and autonomous navigation to prosthetics, robotic radiotherapy, exoskeletons and green energy. See you at the races!