Project description
Enhancing differentiable robot dynamics simulation for pioneering control methods
Differentiable robot dynamics simulation is vital for advanced control methods such as model predictive control and reinforcement learning (RL). Unfortunately, many existing simulators are inefficient due to complex algorithms that make them slower than alternatives such as Pinocchio. With the support of the Marie Skłodowska-Curie Actions programme, the ExTRAORDiNary project aims to enhance differentiable simulation through low-complexity Contact Dynamics Algorithms, efficient software patterns from Pinocchio, and code-generation techniques. The project will address frictional contact challenges without compromising physics and will integrate with the open-source Pinocchio library. It will improve the usability of model predictive control, reinforcement learning, and physics identification, thereby enabling faster whole-body controllers and enhanced RL training, with long-term benefits for biomechanics and computer graphics.
Objective
Differentiable robot dynamics simulation is a crucial enabler of advanced robot control. It is at the heart of both model predictive control (MPC) and learning-based approaches (e.g. reinforcement learning [RL]), which are among the most successful and actively researched robot control algorithms. Increased usage of the computationally demanding MPC/RL controllers has led to a growing need for efficient dynamics simulators. However, existing simulators internally use inefficient high-complexity (worst-case cubic) constrained dynamics algorithms (CDA) and are often inefficiently implemented leading to a slowdown of several factors compared to a fast simulator like Pinocchio.
Addressing these concerns, we will accelerate the differentiable simulation through three complementary strategies. We will 1) leverage low-complexity CDAs, 2) use Pinocchio's proven efficient software design patterns and explore further acceleration via code generation computations, and 3) derive efficient algorithms for differentiating through contact simulation.
Furthermore, our simulator will solve the nonlinear complementarity problem of frictional contact without making physics-compromising relaxations like existing simulators and will be publicly available as part of the widely used open-source Pinocchio library. By adding key enhancements to Pinocchio, we will make it a viable alternative to the inefficient, but feature-rich software simulators. The visibility, impact and usability of our simulator will be enhanced by addressing some low-hanging fruits in MPC, RL and physics identification applications.
This projects contributions will not only pave the way towards fast whole-body controllers and faster and more sustainable RL training (important a time surge of RL research activity), but will also impact adjacent fields like bio-mechanics and computer graphics in the long term
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
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Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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Call for proposal
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(opens in new window) HORIZON-MSCA-2024-PF-01
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78153 Le Chesnay Cedex
France
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