Robust Trajectory Generation and Control for Quadrotor Motion Planning with Field-of-View Control Barrier Certification
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866911244930252800 |
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| author | Pan, Lishuo Catellani, Mattia Sabattini, Lorenzo Ayanian, Nora |
| author_facet | Pan, Lishuo Catellani, Mattia Sabattini, Lorenzo Ayanian, Nora |
| contents | Many approaches to multi-robot coordination are susceptible to failure due to communication loss and uncertainty in estimation. We present a real-time communication-free distributed navigation algorithm certified by control barrier functions, that models and controls the onboard sensing behavior to keep neighbors in the limited field of view for position estimation. The approach is robust to temporary tracking loss and directly synthesizes control to stabilize visual contact through control Lyapunov-barrier functions. The main contributions of this paper are a continuous-time robust trajectory generation and control method certified by control barrier functions for distributed multi-robot systems and a discrete optimization procedure, namely, MPC-CBF, to approximate the certified controller. In addition, we propose a linear surrogate of high-order control barrier function constraints and use sequential quadratic programming to solve MPC-CBF efficiently. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_01009 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Robust Trajectory Generation and Control for Quadrotor Motion Planning with Field-of-View Control Barrier Certification Pan, Lishuo Catellani, Mattia Sabattini, Lorenzo Ayanian, Nora Robotics Many approaches to multi-robot coordination are susceptible to failure due to communication loss and uncertainty in estimation. We present a real-time communication-free distributed navigation algorithm certified by control barrier functions, that models and controls the onboard sensing behavior to keep neighbors in the limited field of view for position estimation. The approach is robust to temporary tracking loss and directly synthesizes control to stabilize visual contact through control Lyapunov-barrier functions. The main contributions of this paper are a continuous-time robust trajectory generation and control method certified by control barrier functions for distributed multi-robot systems and a discrete optimization procedure, namely, MPC-CBF, to approximate the certified controller. In addition, we propose a linear surrogate of high-order control barrier function constraints and use sequential quadratic programming to solve MPC-CBF efficiently. |
| title | Robust Trajectory Generation and Control for Quadrotor Motion Planning with Field-of-View Control Barrier Certification |
| topic | Robotics |
| url | https://arxiv.org/abs/2502.01009 |