FASTER: Fast and Safe Trajectory Planner for Flights in Unknown Environments
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Abstract (arXiv)
High-speed trajectory planning through unknown environments requires algorithmic techniques that enable fast reaction times while maintaining safety as new information about the operating environment is obtained. The requirement of computational tractability typically leads to optimization problems that do not include the obstacle constraints (collision checks are done on the solutions) or use a convex decomposition of the free space and then impose an ad-hoc time allocation scheme for each interval of the trajectory. Moreover, safety guarantees are usually obtained by having a local planner that plans a trajectory with a final "stop" condition in the free-known space. However, these two decisions typically lead to slow and conservative trajectories. We propose FASTER (Fast and Safe Trajectory Planner) to overcome these issues. FASTER obtains high-speed trajectories by enabling the local planner to optimize in both the free-known and unknown spaces. Safety guarantees are ensured by always having a feasible, safe back-up trajectory in the free-known space at the start of each replanning step. Furthermore, we present a Mixed Integer Quadratic Program formulation in which the solver can choose the trajectory interval allocation, and where a time allocation heuristic is computed efficiently using the result of the previous replanning iteration. This proposed algorithm is tested extensively both in simulation and in real hardware, showing agile flights in unknown cluttered environments with velocities up to 3.6 m/s.
Key facts. Cited by 10 papers in the map (data through 13 Oct 2026). First posted on arXiv 8 Mar 2019.
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Citing papers per year: 2021: 4; 2022: 1; 2023: 2; 2024: 1; 2025: 1; 2026: 1.
10 papers.
- 2021Learning High-Speed Flight in the Wildcited by 98
- 2022SABLAS: Learning Safe Control for Black-box Dynamical Systemscited by 17
- 2023A Safer Vision-based Autonomous Planning System for Quadrotor UAVs with Dynamic Obstacle Trajectory Prediction and Its Application with LLMscited by 13
- 2021SABER: Data-Driven Motion Planner for Autonomously Navigating Heterogeneous Robotscited by 4
- 2021What we see and What we don't see: Imputing Occluded Crowd Structures from Robot Sensingcited by 1
- 2023Task-driven Compression for Collision Encoding based on Depth Imagescited by 1
- 2024Multi-robot autonomous 3D reconstruction using Gaussian splatting with Semantic guidancecited by 1
- 2021Advanced Algorithms of Collision Free Navigation and Flocking for Autonomous UAVscited by 0
- 2025Unified Linear Parametric Map Modeling and Perception-aware Trajectory Planning for Mobile Roboticscited by 0
- 2026Personalized Autonomous Driving via Optimal Control with Clearance Constraints from Questionnairescited by 0
- 2026Personalized Autonomous Driving via Optimal Control with Clearance Constraints from Questionnaires9 Feb 2026
- 2025Unified Linear Parametric Map Modeling and Perception-aware Trajectory Planning for Mobile Robotics12 Jul 2025
- 2024Multi-robot autonomous 3D reconstruction using Gaussian splatting with Semantic guidance3 Dec 2024
- 2023A Safer Vision-based Autonomous Planning System for Quadrotor UAVs with Dynamic Obstacle Trajectory Prediction and Its Application with LLMs21 Nov 2023
- 2023Task-driven Compression for Collision Encoding based on Depth Images11 Sep 2023
- 2022SABLAS: Learning Safe Control for Black-box Dynamical Systems6 Jan 2022
- 2021Advanced Algorithms of Collision Free Navigation and Flocking for Autonomous UAVs30 Oct 2021
- 2021Learning High-Speed Flight in the Wild11 Oct 2021
- 2021What we see and What we don't see: Imputing Occluded Crowd Structures from Robot Sensing17 Sep 2021
- 2021SABER: Data-Driven Motion Planner for Autonomously Navigating Heterogeneous Robots3 Aug 2021