Singularity-Avoidance Control of Robotic Systems with Model Mismatch and Actuator Constraints
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arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866912116229799936 |
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| author | Wu, Mingkun Rupenyan, Alisa Corves, Burkhard |
| author_facet | Wu, Mingkun Rupenyan, Alisa Corves, Burkhard |
| contents | Singularities, manifesting as special configuration states, deteriorate robot performance and may even lead to a loss of control over the system. This paper addresses the kinematic singularity concerns in robotic systems with model mismatch and actuator constraints through control barrier functions (CBFs). We propose a learning-based control strategy to prevent robots entering singularity regions. More precisely, we leverage Gaussian process (GP) regression to learn the unknown model mismatch, where the prediction error is restricted by a deterministic bound. Moreover, we offer the criteria for parameter selection to ensure the feasibility of CBFs subject to actuator constraints. The proposed approach is validated by high-fidelity simulations on a 2 degrees-of-freedom (DoFs) planar robot. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2411_07830 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Singularity-Avoidance Control of Robotic Systems with Model Mismatch and Actuator Constraints Wu, Mingkun Rupenyan, Alisa Corves, Burkhard Systems and Control Robotics Singularities, manifesting as special configuration states, deteriorate robot performance and may even lead to a loss of control over the system. This paper addresses the kinematic singularity concerns in robotic systems with model mismatch and actuator constraints through control barrier functions (CBFs). We propose a learning-based control strategy to prevent robots entering singularity regions. More precisely, we leverage Gaussian process (GP) regression to learn the unknown model mismatch, where the prediction error is restricted by a deterministic bound. Moreover, we offer the criteria for parameter selection to ensure the feasibility of CBFs subject to actuator constraints. The proposed approach is validated by high-fidelity simulations on a 2 degrees-of-freedom (DoFs) planar robot. |
| title | Singularity-Avoidance Control of Robotic Systems with Model Mismatch and Actuator Constraints |
| topic | Systems and Control Robotics |
| url | https://arxiv.org/abs/2411.07830 |