Improving local trajectory optimization by enhanced initialization and global guidance

Simple item page
dc.contributor.authorKrämer, Maximilian
dc.contributor.authorBertram, Torsten
dc.date.accessioned2022-04-20T11:16:05Z
dc.date.available2022-04-20T11:16:05Z
dc.date.issued2022-03-14
dc.description.abstractTrajectory optimization is a promising method for planning trajectories of robotic manipulators. With the increasing success of collaborative robots in dynamic environments, the demand for online planning methods grows and offers new opportunities as well as challenges for trajectory optimization. Special requirements in terms of real-time capabilities are one of the greatest difficulties. Optimizing a short planning horizon instead of an entire trajectory is one approach to reduce computation time, which nonetheless separates the optimality of local and global solutions. This contribution introduces, on the one hand, Extended Initialization as a new approach that reduces the risk of local minima and aims at improving the quality of the global trajectory. On the other hand, the particularly critical cases in which local solutions lead to standstills are mitigated by globally guiding local solutions. The evaluation performs four experiments with comparisons to Stochastic Trajectory Optimization for Motion Planning (STOMP) or Probabilistic Roadmap Method (PRM*) and demonstrates the effectiveness of both approaches.en
dc.identifier.urihttp://hdl.handle.net/2003/40867
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-22724
dc.language.isoende
dc.relation.ispartofseriesIEEE access;10
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectMoving horizon planningen
dc.subjectOnline trajectory optimizationen
dc.subjectLocal minimaen
dc.subject.ddc620
dc.titleImproving local trajectory optimization by enhanced initialization and global guidanceen
dc.typeTextde
dc.type.publicationtypearticlede
dcterms.accessRightsopen access
eldorado.secondarypublicationtruede
eldorado.secondarypublication.primarycitationM. Krämer and T. Bertram, "Improving Local Trajectory Optimization by Enhanced Initialization and Global Guidance," in IEEE Access, vol. 10, pp. 29633-29645, 2022, doi: 10.1109/ACCESS.2022.3159233.de
eldorado.secondarypublication.primaryidentifierhttps://doi.org/10.1109/ACCESS.2022.3159233de

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Improving_Local_Trajectory_Optimization_by_Enhanced_Initialization_and_Global_Guidance.pdf
Size:
1.21 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
4.85 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Lehrstuhl fĂĽr Regelungssystemtechnik