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Improved Optimization of Motion Primitives for Motion Planning in State Lattices
Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.ORCID-id: 0000-0002-8354-6249
Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.ORCID-id: 0000-0002-1795-5992
Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.ORCID-id: 0000-0001-6957-2603
2019 (Engelska)Ingår i: 2019 30TH IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV19), 2019, s. 2307-2314Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

In this paper, we propose a framework for generating motion primitives for lattice-based motion planners automatically. Given a family of systems, the user only needs to specify which principle types of motions, which are here denoted maneuvers, that are relevant for the considered system family. Based on the selected maneuver types and a selected system instance, the algorithm not only automatically optimizes the motions connecting pre-defined boundary conditions, but also simultaneously optimizes the end-point boundary conditions as well. This significantly reduces the time consuming part of manually specifying all boundary value problems that should be solved, and no exhaustive search to generate feasible motions is required. In addition to handling static a priori known system parameters, the framework also allows for fast automatic re-optimization of motion primitives if the system parameters change while the system is in use, e.g, if the load significantly changes or a trailer with a new geometry is picked up by an autonomous truck. We also show in several numerical examples that the framework can enhance the performance of the motion planner in terms of total cost for the produced solution.

Ort, förlag, år, upplaga, sidor
2019. s. 2307-2314
Serie
IEEE Intelligent Vehicles Symposium, ISSN 1931-0587, E-ISSN 2642-7214
Nyckelord [en]
Autonomous / Intelligent Robotic Vehicles, Self-Driving Vehicles, Vehicle Control
Nationell ämneskategori
Reglerteknik
Identifikatorer
URN: urn:nbn:se:liu:diva-159657DOI: 10.1109/IVS.2019.8813872ISI: 000508184100306ISBN: 978-1-7281-0560-4 (digital)ISBN: 978-1-7281-0559-8 (tryckt)OAI: oai:DiVA.org:liu-159657DiVA, id: diva2:1394150
Konferens
2019 IEEE Intelligent Vehicles Symposium (IV)
Forskningsfinansiär
Wallenberg AI, Autonomous Systems and Software Program (WASP)
Anmärkning

Funding agencies:This work was partially supported by FFI/VINNOVA and the Wallenberg Artificial Intelligence, Autonomous Systems and Software Program (WASP) funded by Knut and Alice Wallenberg Foundation.

Tillgänglig från: 2019-08-15 Skapad: 2020-02-18 Senast uppdaterad: 2019-08-15

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Bergman, KristofferLjungqvist, OskarAxehill, Daniel
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ReglerteknikTekniska fakulteten
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