2019/03/08 by Jesus Tordesillas, Tordesillas, Jesus, Brett T. Lopez +3 · 3 citations
Computer Science · Engineering · #Air Traffic Management and Optimization #Autonomous Vehicle Technology and Safety #FOS: Computer and information sciences #Robotic Path Planning Algorithms #Robotics (cs.RO)
paper · pdf · doi:10.48550/arxiv.1903.03558
openalex publication_date 2019/03/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
High-speed trajectory planning through unknown environments requires\nalgorithmic techniques that enable fast reaction times while maintaining safety\nas new information about the operating environment is obtained. The requirement\nof computational tractability typically leads to optimization problems that do\nnot include the obstacle constraints (collision checks are done on the\nsolutions) or use a convex decomposition of the free space and then impose an\nad-hoc time allocation scheme for each interval of the trajectory. Moreover,\nsafety guarantees are usually obtained by having a local planner that plans a\ntrajectory with a final "stop" condition in the free-known space. However,\nthese two decisions typically lead to slow and conservative trajectories. We\npropose FASTER (Fast and Safe Trajectory Planner) to overcome these issues.\nFASTER obtains high-speed trajectories by enabling the local planner to\noptimize in both the free-known and unknown spaces. Safety guarantees are\nensured by always having a feasible, safe back-up trajectory in the free-known\nspace at the start of each replanning step. Furthermore, we present a Mixed\nInteger Quadratic Program formulation in which the solver can choose the\ntrajectory interval allocation, and where a time allocation heuristic is\ncomputed efficiently using the result of the previous replanning iteration.\nThis proposed algorithm is tested extensively both in simulation and in real\nhardware, showing agile flights in unknown cluttered environments with\nvelocities up to 3.6 m/s.\n