
RAPTOR
RAPid and robust Trajectory Optimization for Robots
Performing trajectory design for humanoid robots with high degrees of freedom is computationally challenging. The trajectory design process also often involves carefully selecting various hyperparameters and requires a good initial guess which can further complicate the development process. This work introduces a generalized gait optimization framework that directly generates smooth and physically feasible trajectories. The proposed method demonstrates faster and more robust convergence than existing techniques and explicitly incorporates closed-loop kinematic constraints that appear in many modern humanoids.
RAPTOR is smooth.
RAPTOR is robust.
RAPTOR is fast.
RAPTOR directly parameterizes the trajectory in a smooth representation, for example, polynomials, and optimizes on this smooth representation.
Don't know how to initialize the optimization problem? It's okay! RAPTOR can handle it. For humanoid gait optimization problems, we simply assign random initial guesses and RAPTOR can still converge to feasible solutions!
RAPTOR is fully implemented in C++. It is able to solve the humanoid gait optimization problems in seconds!
Trajectory Optimization Demos
Digit-v3 walking.
Talos walking.
Unitree G1 walking.
Kinova-gen3
Exciting trajectories for more accurate system identification while ensuring robot safety.
Code and documentation are available here.
Identifying inertial parameters of end effector online to stack unknown dumbbells vertically on a specific location.
Code and documentation are available here.
Solving a series of inverse kinematics in seconds!
Code and documentation are available here.
Links
Authors
1 Robotics Institute, University of Michigan, Ann Arbor 2 Mechanical Engineering, University of Michigan, Ann Arbor
This work is developed under RoahmLab.
BibTeX
@article{zhang2024rapidrobusttrajectoryoptimization,
title={Rapid and Robust Trajectory Optimization for Humanoids},
author={Bohao Zhang and Ram Vasudevan},
journal={arXiv preprint arXiv:2409.00303},
year={2024}
}
Contact
We are actively developing the codebase and appreciate any feedback!
If you have any questions about the paper, please feel free to contact Bohao Zhang.
If you have any questions about the code and would like to report any bugs or problems, please raise a new issue in the Issues page in the RAPTOR repo. We will try to respond to it as soon as possible.
If you would like to request any related new features and have suggestions on how to improve the performance of RAPTOR, please raise a new discussion in the Discussions page in the RAPTOR repo.
Related Projects
ARMOUR - Autonomous Robust Manipulation via Optimization with Uncertainty-aware ReachabilityWAITR - Wrench Analysis for Inertial Transport using Reachability
SPARROWS - Safe Planning for Articulated Robots Using Reachability-based Obstacle Avoidance With Spheres