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Receding-Horizon La...
Receding-Horizon Lattice-based Motion Planning with Dynamic Obstacle Avoidance
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- Andersson, Olov, 1979- (författare)
- Linköpings universitet,Artificiell intelligens och integrerade datorsystem,Tekniska fakulteten,KPLAB
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- Ljungqvist, Oskar, 1990- (författare)
- Linköpings universitet,Reglerteknik,Tekniska fakulteten
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- Tiger, Mattias, 1989- (författare)
- Linköpings universitet,Artificiell intelligens och integrerade datorsystem,Tekniska fakulteten,KPLAB
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visa fler...
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- Axehill, Daniel, 1978- (författare)
- Linköpings universitet,Reglerteknik,Tekniska fakulteten
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- Heintz, Fredrik, 1975- (författare)
- Linköpings universitet,Artificiell intelligens och integrerade datorsystem,Tekniska fakulteten,KPLAB
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(creator_code:org_t)
- Institute of Electrical and Electronics Engineers (IEEE), 2018
- 2018
- Engelska.
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Ingår i: 2018 IEEE Conference on Decision and Control (CDC). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781538613955 - 9781538613948 - 9781538613962 ; , s. 4467-4474
- Relaterad länk:
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https://liu.diva-por... (primary) (Raw object)
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- A key requirement of autonomous vehicles is the capability to safely navigate in their environment. However, outside of controlled environments, safe navigation is a very difficult problem. In particular, the real-world often contains both complex 3D structure, and dynamic obstacles such as people or other vehicles. Dynamic obstacles are particularly challenging, as a principled solution requires planning trajectories with regard to both vehicle dynamics, and the motion of the obstacles. Additionally, the real-time requirements imposed by obstacle motion, coupled with real-world computational limitations, make classical optimality and completeness guarantees difficult to satisfy. We present a unified optimization-based motion planning and control solution, that can navigate in the presence of both static and dynamic obstacles. By combining optimal and receding-horizon control, with temporal multi-resolution lattices, we can precompute optimal motion primitives, and allow real-time planning of physically-feasible trajectories in complex environments with dynamic obstacles. We demonstrate the framework by solving difficult indoor 3D quadcopter navigation scenarios, where it is necessary to plan in time. Including waiting on, and taking detours around, the motions of other people and quadcopters.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)
Nyckelord
- Motion Planning
- Optimal Control
- Autonomous System
- UAV
- Dynamic Obstacle Avoidance
- Robotics
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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