Fast and Scalable Algorithms for Robot Simulation and Control
This talk presents recent algorithmic advances that accelerate robot dynamics simulation and control by exploiting structure and reducing computational complexity. We introduce a family of low-complexity algorithms for simulating constrained rigid-body systems, including novel recursive methods that can address kinematic loops and are robust to singularities. Building on these foundations, we show how these algorithms lead to fast and scalable solutions to core robotics problems such as differential inverse kinematics, frictional contact simulation and trajectory optimization. Together, these contributions enable efficient online computation for control and planning in high-dimensional robotic systems.
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Seminar Room, EEE Dept
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Guwahati, Assam
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India
781039
Speakers
Ajay
Topic:
Fast and Scalable Algorithms for Robot Simulation and Control
This talk presents recent algorithmic advances that accelerate robot dynamics simulation and control by exploiting structure and reducing computational complexity. We introduce a family of low-complexity algorithms for simulating constrained rigid-body systems, including novel recursive methods that can address kinematic loops and are robust to singularities. Building on these foundations, we show how these algorithms lead to fast and scalable solutions to core robotics problems such as differential inverse kinematics, frictional contact simulation and trajectory optimization. Together, these contributions enable efficient online computation for control and planning in high-dimensional robotic systems.
Biography:
Bio of the Speaker: Ajay Sathya received his Bachelor's degree from NITK Surathkal, India, in 2016, and both his Master's and Ph.D. degrees from KU Leuven, Belgium, in 2018 and 2023 respectively, all in mechanical engineering. He is a Marie Skłodowska-Curie Postdoctoral Fellow in the Willow research team at Inria and École Normale Supérieure, Paris, France. His current research focuses on developing scalable algorithms for differentiable simulation and control of high-dimensional robots operating in contact-rich environments. His work has been recognized with several awards, including the IEEE RA-L 2024 Best Paper Award, IROS 2023 Best Paper Finalist, and the IEEE RAS Technical Committee on Model-Based Optimization Best Paper Award (2024). He has also been selected as a Robotics: Science and Systems Pioneer (2024).
