Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
157 tokens/sec
GPT-4o
43 tokens/sec
Gemini 2.5 Pro Pro
43 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Hierarchical Fault-Tolerant Coverage Control for an Autonomous Aerial Agent (2404.09838v1)

Published 15 Apr 2024 in eess.SY and cs.SY

Abstract: Fault-tolerant coverage control involves determining a trajectory that enables an autonomous agent to cover specific points of interest, even in the presence of actuation and/or sensing faults. In this work, the agent encounters control inputs that are erroneous; specifically, its nominal controls inputs are perturbed by stochastic disturbances, potentially disrupting its intended operation. Existing techniques have focused on deterministically bounded disturbances or relied on the assumption of Gaussian disturbances, whereas non-Gaussian disturbances have been primarily been tackled via scenario-based stochastic control methods. However, the assumption of Gaussian disturbances is generally limited to linear systems, and scenario-based methods can become computationally prohibitive. To address these limitations, we propose a hierarchical coverage controller that integrates mixed-trigonometric-polynomial moment propagation to propagate non-Gaussian disturbances through the agent's nonlinear dynamics. Specifically, the first stage generates an ideal reference plan by optimising the agent's mobility and camera control inputs. The second-stage fault-tolerant controller then aims to follow this reference plan, even in the presence of erroneous control inputs caused by non-Gaussian disturbances. This is achieved by imposing a set of deterministic constraints on the moments of the system's uncertain states.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (24)
  1. Receding horizon path planning for 3d exploration and surface inspection. Autonomous Robots, 42, 291–306.
  2. Survey on coverage path planning with unmanned aerial vehicles. Drones, 3(1), 4.
  3. Robust model predictive control via scenario optimization. IEEE Transactions on Automatic Control, 58(1), 219–224.
  4. A minimalist algorithm for multirobot continuous coverage. IEEE Transactions on Robotics, 27(2), 297–312.
  5. Choset, H. (2000). Coverage of known spaces: The boustrophedon cellular decomposition. Autonomous Robots, 9(3), 247–253.
  6. Chance constrained motion planning for high-dimensional robots. In Proc. IEEE Int. Conf. on Robot. and Aut. (ICRA), 8805–8811.
  7. A survey on coverage path planning for robotics. Robotics and Autonomous Systems, 61(12), 1258–1276.
  8. Non-gaussian risk bounded trajectory optimization for stochastic nonlinear systems in uncertain environments. In Proc. IEEE International Conference on Robotics and Automation (ICRA), 11044–11050.
  9. Huang, W.H. (2001). Optimal line-sweep-based decompositions for coverage algorithms. In Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation, volume 1, 27–32. IEEE.
  10. Time-efficient and complete coverage path planning based on flow networks for multi-robots. International Journal of Control, Automation and Systems, 11(2), 369–376.
  11. Moment-based exact uncertainty propagation through nonlinear stochastic autonomous systems. arXiv preprint arXiv:2101.12490 [eess.SY].
  12. Research on the coverage path planning of uavs for polygon areas. In 2010 5th IEEE Conference on Industrial Electronics and Applications, 1467–1472.
  13. Chance-constrained sequential convex programming for robust trajectory optimization. In Proc. IEEE European Control Conference (ECC), 1871–1878.
  14. Coverage path planning for UAVs based on enhanced exact cellular decomposition method. Mechatronics, 21(5), 876–885.
  15. Robust model predictive control of constrained linear systems with bounded disturbances. Automatica, 41(2), 219–224.
  16. A one-sided vysochanskii-petunin inequality with financial applications. European Journal of Operational Research, 295(1), 374–377.
  17. Distributed estimation and control for jamming an aerial target with multiple agents. IEEE Transactions on Mobile Computing, 22(12), 7203–7217.
  18. Integrated ray-tracing and coverage planning control using reinforcement learning. In 2022 IEEE 61st Conference on Decision and Control (CDC), 7200–7207. IEEE.
  19. Enhanced discrete particle swarm optimization path planning for uav vision-based surface inspection. Automation in Construction, 81, 25–33.
  20. Summers, T. (2018). Distributionally robust sampling-based motion planning under uncertainty. In Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 6518–6523.
  21. Taubin, G. (2011). 3d rotations. IEEE Computer Graphics and Applications, 31(6), 84–89.
  22. Autonomous 4D trajectory planning for dynamic and flexible air traffic management. Journal of Intelligent & Robotic Systems, 106(1), 11.
  23. Path planning for uav to cover multiple separated convex polygonal regions. IEEE Access, 8, 51770–51785.
  24. Efficient complete coverage of a known arbitrary environment with applications to aerial operations. Autonomous Robots, 36(4), 365–381.
Citations (1)

Summary

We haven't generated a summary for this paper yet.