A System for 3D Autonomous Rotorcraft Navigation in Urban Environments

Tsenkov, Peter; Howlett, Jason K.; Whalley, Matthew S.; Schulein, Greg; Takahashi, Marc D.; Rhinehart, Matthew H.; May, Berenice F Mettler

doi:10.2514/6.2008-7412

Cited by 20 publications

(22 citation statements)

References 26 publications

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“…This can be solved by iteratively refining the smoothed path or resorting to fallback mechanisms as described in refs. [2,24,31].…”

Section: Related Workmentioning

confidence: 99%

“…[31] an approach to account for the rotorcraft's velocity when replanning during flight is presented. In order to allow a smooth transition to the replanned path, the start point of this path is moved beyond the helicopter's minimum stopping distance and within its dynamically reachable set.…”

Section: Related Workmentioning

confidence: 99%

“…In refs. [19,31] a velocity profile is used to assess the path's dynamic feasibility in respect to a simplified kinematic model. This profile is used by the path tracking controller to ensure sufficient maneuverability to track the path and compensate disturbances.…”

Section: Related Workmentioning

confidence: 99%

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Online Replanning of Time-Efficient Flight Paths for Unmanned Rotorcraft

Schopferer¹,

Adolf²

2015

J Intell Robot Syst

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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.

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“…This can be solved by iteratively refining the smoothed path or resorting to fallback mechanisms as described in refs. [2,24,31].…”

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Online Replanning of Time-Efficient Flight Paths for Unmanned Rotorcraft

Schopferer¹,

Adolf²

2015

J Intell Robot Syst

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“…Even though the latter is more popular because the graph is easier to construct, it becomes very computationally heavy for fine resolutions. Multi-resolution methods have effectively overcome this problem, for example, unmanned helicopters have been flown by Tsenkov et al [4] and Whalley et al [5] using a quad-tree grid representation and performing A* search. However, such methods still incur discretization errors and produce unnatural oblique paths.…”

Section: Related Workmentioning

confidence: 99%

Sparse Tangential Network (SPARTAN): Motion planning for micro aerial vehicles

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Choudhury

Scherer

et al. 2013

2013 IEEE International Conference on Robotics and Automation

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Abstract-Micro aerial vehicles operating outdoors must be able to maneuver through both dense vegetation and across empty fields. Existing approaches do not exploit the nature of such an environment. We have designed an algorithm which plans rapidly through free space and is efficiently guided around obstacles. In this paper we present SPARTAN (Sparse Tangential Network) as an approach to create a sparsely connected graph across a tangential surface around obstacles. We find that SPARTAN can navigate a vehicle autonomously through an outdoor environment producing plans 172 times faster than the state of the art (RRT*). As a result SPARTAN can reliably deliver safe plans, with low latency, using the limited computational resources of a lightweight aerial vehicle.

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“…without a priori information about terrain elevation and obstacles, the following three capabilities are essential for an autonomous helicopter: (1) ground detection and terrain following; (2) obstacle detection and avoidance; and (3) stable, effective control. Autonomous flights with unmanned helicopters close to ground and obstacles have been successfully demonstrated by (Scherer et al, 2008) and (Tsenkov et al, 2008). However, it is unclear if the helicopters can safely be operated beyond visual range without a backup pilot.…”

Section: Introductionmentioning

confidence: 99%

Autonomous Unmanned Helicopter System for Remote Sensing Missions in Unknown Environments

Merz

Chapman

2012

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:This paper presents the design of an autonomous unmanned helicopter system for low-altitude remote sensing. The proposed concepts and methods are generic and not limited to a specific helicopter. The development was driven by the need for a dependable, modular, and affordable system with sufficient payload capacity suitable for both research and real-world deployment. The helicopter can be safely operated without a backup pilot in a contained area beyond visual range. This enables data collection in inaccessible or dangerous areas. Thanks to its terrain following and obstacle avoidance capability, the system does not require a priori information about terrain elevation and obstacles. Missions are specified in state diagrams and flight plans. We present performance characteristics of our system and show results of its deployment in real-world scenarios. We have successfully completed several dozen infrastructure inspection missions and crop monitoring missions facilitating plant phenomics studies.

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A System for 3D Autonomous Rotorcraft Navigation in Urban Environments

Cited by 20 publications

References 26 publications

Online Replanning of Time-Efficient Flight Paths for Unmanned Rotorcraft

Online Replanning of Time-Efficient Flight Paths for Unmanned Rotorcraft

Sparse Tangential Network (SPARTAN): Motion planning for micro aerial vehicles

Autonomous Unmanned Helicopter System for Remote Sensing Missions in Unknown Environments

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