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Real-Time Constrained Nonlinear Model Predictive Control on SO(3) for Dynamic Legged Locomotion
- Source :
- IROS
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
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Abstract
- This paper presents a constrained nonlinear model predictive control (NMPC) framework for legged locomotion. The framework assumes a legged robot as a floating base single rigid body with contact forces being applied to the body as external forces. With consideration of orientation dynamics evolving on the rotation manifold SO(3), analytic Jacobians which are necessary for constructing the gradient and the Gauss-Newton Hessian approximation of the objective function are derived. This procedure also includes the reparameterization of the robot orientation on SO(3) to orientation error in the tangent space of that manifold. Obtained gradient and Gauss-Newton Hessian approximation are utilized to solve nonlinear least squares problems formulated from NMPC in a computationally efficient manner. The proposed algorithm is verified on various types of legged robots and gaits in a simulation environment.
- Subjects :
- Hessian matrix
0209 industrial biotechnology
021103 operations research
Computer science
0211 other engineering and technologies
02 engineering and technology
Rigid body
Gait
Contact force
Computer Science::Robotics
Model predictive control
symbols.namesake
020901 industrial engineering & automation
Control theory
Non-linear least squares
Orientation (geometry)
Tangent space
symbols
Robot
Legged robot
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
- Accession number :
- edsair.doi...........7b14b87dae5ddff9c57ffb690457853b