Collaborative Research: CISE-EPSRC: Efficient Constraint-Based Musculotendon Simulation for Biomechanically Accurate Characters

About This Grant

This project will create a new class of computational tools for physiologically accurate human motion simulation by bridging the critical gap between computer graphics and biomechanics. Simulation methods in computer graphics have historically prioritized computational efficiency and visually compelling results for animations and virtual experiences, often at the expense of physical accuracy. Conversely, biomechanical simulations emphasize realism and experimental validation but tend to be slower, more specialized, and less adaptable to interactive applications. By combining the strengths of both fields, the project will result in simulation methods that are fast, general-purpose, and physiologically grounded. This work will open the door to new cross-disciplinary collaborations, providing movement scientists in fields such as sports, health, and rehabilitation with tools to simulate complex, real-world movements that were previously infeasible. The resulting validated models can enhance training simulators and, when combined with existing open-source physics engines, will create new avenues for high-fidelity simulation and modeling in applications ranging from robotics to gaming. This project will deliver a next-generation, open-source physics simulator that accurately models musculotendon dynamics for graphics and other fields. To achieve this, the project explores four research thrusts. The first thrust establishes a unified, constraint-based simulation framework that treats muscles, tendons, skeletal structures, and environmental contacts as a coupled, fully implicit system. This formulation enables stable and accurate simulation of complex, high-contact human motion while maintaining physiological realism. The second thrust addresses muscle-based control by leveraging reinforcement learning to train neuromuscular controllers that produce realistic activation patterns, improving upon traditional joint-actuation systems/models that often generate unnatural and/or biomechanically implausible motions. The third thrust focuses on validation, using in-vivo biomechanical and physiological data, as well as benchmarking against existing simulation tools, to evaluate both the accuracy and computational performance of the system. The fourth thrust demonstrates broad applicability by enabling physiologically informed animation, injury-aware motion planning, and optimization of complex, contact-rich tasks. The resulting simulation platform is expected to support research and development across disciplines, contributing to improved understanding of human movement, better tools for clinical and biomechanical analysis, and enhanced realism in interactive systems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.