Abstract
Swarm robotics presents challenges in trajectory control due to the complex paths followed by individual robots. This study addresses the issue by proposing a fuzzy neuro-control system that provides improved performance for each robot. The goal is to achieve successful trajectory tracking in a collaborative robot environment; however, the system's effectiveness relies on a finite and controlled setting. An impedance-based learning approach is integrated to enhance robot interaction and detect external elements. Artificial intelligence methodologies are employed for planning, control, and trajectory tracking in a dynamic environment. The methodology includes designing specific and finite trajectories, training the neuro-fuzzy system based on the leader's trajectory, and evaluating follower robot behaviors with different trajectories and distances from the leader using Georgia Tech's Robotarium platform. The platform offers a user-friendly interface, simulation capabilities, short response times, and free access for real-time algorithm implementation. The results validate the effectiveness of the proposed approach, considering the limitations of the control used, while highlighting its potential for swarm robotics research.
Original language | English |
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Title of host publication | 1st IEEE Colombian Caribbean Conference, C3 2023 |
Editors | Paul Sanmartin Mendoza, Andres Navarro |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9798350341799 |
DOIs | |
State | Published - 2023 |
Event | 1st IEEE Colombian Caribbean Conference, C3 2023 - Barranquilla, Colombia Duration: 22 Nov 2023 → 25 Nov 2023 |
Publication series
Name | 1st IEEE Colombian Caribbean Conference, C3 2023 |
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Conference
Conference | 1st IEEE Colombian Caribbean Conference, C3 2023 |
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Country/Territory | Colombia |
City | Barranquilla |
Period | 22/11/23 → 25/11/23 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
Keywords
- collaborative robotics
- navigation
- neuro-fuzzy
- Robotarium
- task execution