ONLINE and multi-objective trajectory planner for robotic systems

Abstract Advancements in automation technology have led to the increased utilization of industrial robots in manufacturing processes. Trajectory planning, which is crucial in robotics, involves designing smooth trajectories that adhere to constraints. Trajectory planning methods can be classified as...

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Main Authors: Habib Mohamad, Sadjaad Ozgoli
Format: Article
Language:English
Published: Springer 2025-01-01
Series:Discover Applied Sciences
Subjects:
Online Access:https://doi.org/10.1007/s42452-024-06431-x
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author Habib Mohamad
Sadjaad Ozgoli
author_facet Habib Mohamad
Sadjaad Ozgoli
author_sort Habib Mohamad
collection DOAJ
description Abstract Advancements in automation technology have led to the increased utilization of industrial robots in manufacturing processes. Trajectory planning, which is crucial in robotics, involves designing smooth trajectories that adhere to constraints. Trajectory planning methods can be classified as either kinematic or dynamic, with dynamic models providing improved capacity utilization but requiring greater complexity. Given the need for efficient real-time implementation with low computational demands, the kinematic method is indispensable. The challenge lies in finding a balance between swift movements and minimal vibration, as smoother trajectories often necessitate higher-order polynomials, resulting in longer execution times and more intricate computations. Addressing the trade-off between speed and smoothness is crucial, as trajectory planning effectiveness depends on balancing energy efficiency, smooth motion, and computational complexity. A novel trajectory planner for point-to-point movements has been developed to enable rapid and smooth motion by integrating the advantages of minimum acceleration and minimum jerk trajectories. This innovative approach, tailored for a diverse range of robotic systems, generates a multi-objective and optimized trajectory as a single segment for seamless online implementation. Simulation and experimental tests were conducted to evaluate the proposed trajectory planner, comparing its performance against commonly used methods in terms of velocity, energy consumption, and smoothness.
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spelling doaj-art-aece458ebeab4e24aa0cc997d8413b132025-08-20T02:36:40ZengSpringerDiscover Applied Sciences3004-92612025-01-017111310.1007/s42452-024-06431-xONLINE and multi-objective trajectory planner for robotic systemsHabib Mohamad0Sadjaad Ozgoli1Department of Electrical and Computer Engineering, Tarbiat Modares UniversityDepartment of Electrical and Computer Engineering, Tarbiat Modares UniversityAbstract Advancements in automation technology have led to the increased utilization of industrial robots in manufacturing processes. Trajectory planning, which is crucial in robotics, involves designing smooth trajectories that adhere to constraints. Trajectory planning methods can be classified as either kinematic or dynamic, with dynamic models providing improved capacity utilization but requiring greater complexity. Given the need for efficient real-time implementation with low computational demands, the kinematic method is indispensable. The challenge lies in finding a balance between swift movements and minimal vibration, as smoother trajectories often necessitate higher-order polynomials, resulting in longer execution times and more intricate computations. Addressing the trade-off between speed and smoothness is crucial, as trajectory planning effectiveness depends on balancing energy efficiency, smooth motion, and computational complexity. A novel trajectory planner for point-to-point movements has been developed to enable rapid and smooth motion by integrating the advantages of minimum acceleration and minimum jerk trajectories. This innovative approach, tailored for a diverse range of robotic systems, generates a multi-objective and optimized trajectory as a single segment for seamless online implementation. Simulation and experimental tests were conducted to evaluate the proposed trajectory planner, comparing its performance against commonly used methods in terms of velocity, energy consumption, and smoothness.https://doi.org/10.1007/s42452-024-06431-xRobotic systemsOptimal controlMulti-objective trajectoryTrajectory planning
spellingShingle Habib Mohamad
Sadjaad Ozgoli
ONLINE and multi-objective trajectory planner for robotic systems
Discover Applied Sciences
Robotic systems
Optimal control
Multi-objective trajectory
Trajectory planning
title ONLINE and multi-objective trajectory planner for robotic systems
title_full ONLINE and multi-objective trajectory planner for robotic systems
title_fullStr ONLINE and multi-objective trajectory planner for robotic systems
title_full_unstemmed ONLINE and multi-objective trajectory planner for robotic systems
title_short ONLINE and multi-objective trajectory planner for robotic systems
title_sort online and multi objective trajectory planner for robotic systems
topic Robotic systems
Optimal control
Multi-objective trajectory
Trajectory planning
url https://doi.org/10.1007/s42452-024-06431-x
work_keys_str_mv AT habibmohamad onlineandmultiobjectivetrajectoryplannerforroboticsystems
AT sadjaadozgoli onlineandmultiobjectivetrajectoryplannerforroboticsystems