An Abductive Reasoning Approach for Energy Saving in Robotic Systems

The velocity and acceleration commands of industrial robots are set to their maximum values to shorten the cycle time of products. However, the excessively high speed and acceleration for movements can cause unnecessary mechanical energy and electricity consumption. This paper proposes an energy-saving approach for robotic systems based on abductive reasoning. Results for different combinations of speed commands and acceleration commands are evaluated based on energy consumption and cycle time. Moreover, a well-designed abduction rule formula is used to achieve a good balance between cycle time and mechanical energy consumption of industrial robots. Simulation results of a Franka robot by ROS, Gazebo, and Moveit verify the effectiveness of the proposed approach.

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Publication Details

Journal
Emerging Science Innovation
Published
2025-05-15
DOI
https://doi.org/10.46604/emsi.2024.14475
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.00
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article

An Abductive Reasoning Approach for Energy Saving in Robotic Systems

Ju-Feng Wu, Ming-Yang Cheng
Emerging Science Innovation
Robotic Path Planning Algorithms
article

An Abductive Reasoning Approach for Energy Saving in Robotic Systems

Ju-Feng Wu, Ming-Yang Cheng
article en

Abstract

The velocity and acceleration commands of industrial robots are set to their maximum values to shorten the cycle time of products. However, the excessively high speed and acceleration for movements can cause unnecessary mechanical energy and electricity consumption. This paper proposes an energy-saving approach for robotic systems based on abductive reasoning. Results for different combinations of speed commands and acceleration commands are evaluated based on energy consumption and cycle time. Moreover, a well-designed abduction rule formula is used to achieve a good balance between cycle time and mechanical energy consumption of industrial robots. Simulation results of a Franka robot by ROS, Gazebo, and Moveit verify the effectiveness of the proposed approach.

Emerging Science InnovationVol. 5
National Cheng Kung University (TW)
Openalex Percentile: Top 78%
Robotic Path Planning Algorithms
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