Majid Khadiv

Short Biography

Prof. Majid Khadiv’s (*1988) research interests include planning, control and learning for robotic systems, with an emphasis on locomotion and manipulation. His research goal is to develop theoretical frameworks that enable a loco-manipulation system to autonomously interact with the environment and continuously learn from these interactions. Experimental validation of developed algorithms on real robots is also an important axis of his research.

Prof. Khadiv received his PhD from K. N. Toosi University of Technology in 2017. During his PhD, he led for three years the dynamics and control team in the Iranian national humanoid robotics project, Surena III, and also visited for one year the Max Planck Institute for Intelligent Systems (MPI-IS). From 2018-2023, he was a research scientist at the MPI-IS. In September 2023, Prof. Khadiv was appointed to the professorship for AI Planning in Dynamic Environments at TUM and the Munich Institute of Robotics and Machine Intelligence (MIRMI).

Predictive control and learning for whole-body motion generation

The past few years has witnessed a significant progress in the field of legged locomotion. This is mainly due to the availability of high-performance torque-controlled platforms as well as development of algorithms that scale to high-dimensional, hybrid and under-actuated systems. In this talk, I will present my recent research efforts mainly on the algorithmic side, with an emphasis on developing efficient predictive controllers that can be complemented with supervised/reinforcement learning for real-time execution in the real world. I will also share my perspective on the open problems that we still need to solve to have functional humanoid robots in the real world.