Improving Local Trajectory Optimization by Enhanced Initialization and Global Guidance

Trajectory 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. S...

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Main Authors: Maximilian Kramer, Torsten Bertram
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9733921/
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author Maximilian Kramer
Torsten Bertram
author_facet Maximilian Kramer
Torsten Bertram
author_sort Maximilian Kramer
collection DOAJ
description Trajectory 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.
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spelling doaj.art-3016077a28a74ea9875d59223d0270c72022-12-21T22:09:46ZengIEEEIEEE Access2169-35362022-01-0110296332964510.1109/ACCESS.2022.31592339733921Improving Local Trajectory Optimization by Enhanced Initialization and Global GuidanceMaximilian Kramer0https://orcid.org/0000-0003-0179-0684Torsten Bertram1Institute of Control Theory and Systems Engineering, TU Dortmund University, Dortmund, GermanyInstitute of Control Theory and Systems Engineering, TU Dortmund University, Dortmund, GermanyTrajectory 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.https://ieeexplore.ieee.org/document/9733921/Moving horizon planningonline trajectory optimizationlocal minima
spellingShingle Maximilian Kramer
Torsten Bertram
Improving Local Trajectory Optimization by Enhanced Initialization and Global Guidance
IEEE Access
Moving horizon planning
online trajectory optimization
local minima
title Improving Local Trajectory Optimization by Enhanced Initialization and Global Guidance
title_full Improving Local Trajectory Optimization by Enhanced Initialization and Global Guidance
title_fullStr Improving Local Trajectory Optimization by Enhanced Initialization and Global Guidance
title_full_unstemmed Improving Local Trajectory Optimization by Enhanced Initialization and Global Guidance
title_short Improving Local Trajectory Optimization by Enhanced Initialization and Global Guidance
title_sort improving local trajectory optimization by enhanced initialization and global guidance
topic Moving horizon planning
online trajectory optimization
local minima
url https://ieeexplore.ieee.org/document/9733921/
work_keys_str_mv AT maximiliankramer improvinglocaltrajectoryoptimizationbyenhancedinitializationandglobalguidance
AT torstenbertram improvinglocaltrajectoryoptimizationbyenhancedinitializationandglobalguidance