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All Journal IAES International Journal of Robotics and Automation (IJRA)
Daffa, Muhammad Fariz
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Automotive Engineering Electrical & Electronics Engineering

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Robot navigation on inclined terrain using social force model Daffa, Muhammad Fariz; Dewantara, Bima Sena Bayu; Setiawardhana, Setiawardhana
IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v13i2.pp131-139

Abstract

This research introduces an innovative approach to address the limitations of the commonly used social force model-based robot navigation method on flat terrain when applied to sloped terrain. The incline of the terrain becomes a crucial factor in calculating the robot’s steering output when navigating from the initial position to the target position while avoiding obstacles. Therefore, we propose a social forced model-based robot navigation system that can adapt to inclined terrain using inertial measurement unit sensor assistance. The system can detect the surface incline in real time and dynamically adjust friction and gravitational forces, ensuring the robot’s speed and heading direction are maintained. Simulation results conducted using CoppeliaSim show a significant improvement in speed adjustment efficiency. With this new navigation system, the robot can reach its destination in 59.935089 seconds, compared to the conventional social forced model which takes 63.506442 seconds, the robot is also able to reduce slip to reduce wasted movement. This method shows the potential of implementing a faster and more efficient navigation system in the context of inclined terrain.
Co-Authors Bima Sena Bayu Dewantara Setiawardhana, Setiawardhana