Online Replanning of Time-Efficient Flight Paths for Unmanned Rotorcraft

Abstract

Onboard and online flight path planning for small-scale unmanned rotorcraft requires efficient algorithms in order to meet real-time constraints. In a priori unknown environment, rapid replanning is necessary in order to maintain a safe clearance when new obstacles are detected. The complexity of the planning problem varies vastly with the required flight path qualities and the complexity of the environment.In most scenarios flight paths should be smooth and time-efficient and always feasible to fly. Therefore, the rotorcraft's flight dynamics must be accounted for. Decoupled planning approaches have been proven to solve this problem very efficiently by dividing the problem into sequentially solvable subproblems. However, this computational efficiency comes at the cost of having to compromise on the flight path quality. In this work, we present a decoupled planning approach that has been integrated with our midiARTIS helicopter in order to perform onboard path planning when flying through a priori unknown environment. The approach involves roadmap-based global path planning and local path refinement with cubic splines. It allows to plan safe, dynamically feasible and timeefficient flight paths with limited onboard processing power. We present simulation results from a set of benchmark scenarios in complex urban terrain as well as results from flight testing of a closed-loop obstacle avoidance maneuver with virtual obstacle mapping. Our results demonstrate that close-to-optimal flight paths can be planned with a decoupled planning approach, if heuristics and simplifications for each planning step are carefully chosen.

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

“…For instance, our search included, but was not limited to, such terms as “unmanned aerial vehicle,” “UAV,” “drone,” “unmanned aircraft,” “unmanned aerial system,” “UAS,” “remotely piloted aircraft,” and “remotely piloted vehicle.” Note that operations planning of drones are closely related to more general topics, such as operations planning of mobile robots (including ground‐based drones) and mobile sensors as well as vehicle routing and machine scheduling, which are not part of this survey. We consider complex drone operations that usually involve several tasks. Thus, we do not include articles on obstacle‐avoiding path planning from a given starting point to a given end point or on planning trajectories of drones flying in formation . We refer the interested reader to the work of Goerzen et al , Khaksar et al and Yang et al on path planning problems. We survey articles that formulate an optimization problem, describing objective functions, decision variables, and the set of feasible solutions.…”