Bioptim

Bioptim performs musculoskeletal optimal control in biomechanics to analyze movement disorders, estimate non-measurable physiological quantities, and investigate human movement optimality via musculoskeletal simulations.

Key Features:

• Algorithmic Differentiation: Uses algorithmic differentiation to compute exact derivatives for optimization problems.
• Multiple Shooting Formulation: Employs a multiple shooting formulation to enforce dynamic consistency across phases.
• Nonlinear Solver Integration: Interfaces with nonlinear solvers to compute optimal control solutions.
• C++ Core for Performance: Implements a C++ core to enhance computational efficiency of numerical computations.
• Muscle-Driven and Torque-Driven Dynamics: Supports both muscle-driven and torque-driven musculoskeletal models.
• Multiphase Problem Solving: Handles multiphase simulations and transitions between dynamic phases.
• Motion Tracking and Prediction: Performs motion tracking and predictive simulation of movement trajectories.
• Parameter Optimization: Enables optimization of model parameters within optimal control problems.
• Real-Time Estimation and Control: Supports moving horizon estimation and model predictive control for real-time applications.
• Quaternion-Based Rotational Dynamics: Handles quaternion representations for rotational movements.
• Objective Functions and Constraints: Accommodates diverse objective functions and constraints to shape optimization problems.
• Estimation of Physiological Quantities: Facilitates estimation of non-measurable physiological quantities such as muscle forces.

Scientific Applications:

• Movement Disorder Analysis: Analyzes movement disorders using musculoskeletal optimal control simulations.
• Estimation of Muscle Forces: Estimates non-measurable muscle forces, including via upper-limb real-time moving horizon estimation.
• Gait Simulation: Simulates multiphase muscle-driven gait cycles for data-driven investigations.
• Predictive Task Simulation: Performs predictive muscle-driven simulations such as pointing tasks.
• Rotational Motion Modeling: Models complex rotational movements exemplified by a twisting somersault using quaternions.
• External Force Control: Implements position controllers that utilize external forces in simulations.
• Maximum-Height Jump Simulation: Simulates multiphase torque-driven maximum-height jump motions.
• Model Predictive Control Research: Applies model predictive control to study and control dynamic human movement.

Methodology:

Bioptim uses algorithmic differentiation, a multiple shooting optimal control formulation, integration with nonlinear solvers, and a C++ computational core.