TY - GEN
T1 - On the Effectiveness of Torque Sensor on Cooperative Transport for Robot Swarm
AU - Alkilabi, Muhanad
AU - Alnasrawi, Ali Mohammed R.
AU - Kadhim, Huda Ragheb
AU - Almansoori, Ahmed
AU - Tuci, Elio
N1 - Funding Information:
The authors of this research would like to thank the University of Kerbala to make this research possible.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Cooperative transport in swarm robotics is particularly challenging because the group coordination needs to be generated without using centralized control, global information and any form of direct communication. This study investigates a simple scenario for cooperative object transport in robotics swarm. The aim is to investigate the effects of torque sensors on generating effective group transport strategies for a robot swarm. The torque sensor is simulated by reading the torque feedback from Bullet physical engine hinge constraint which connects every wheel to the body of the robot. In this simulated study, a group of two agents controlled by a dynamic neural network shaped by artificial evolution are required to transport an elongate cuboid object which cannot move by single agent. We examine the flexibility of best evolved controller against different classes of object mass and size. The evolved controller exhibits a re-orientation, re-position and communicating forces through the object behaviors analogous to those observed in a biological ant. In spite of task complexity, the results demonstrate a decent performance in term of adaptability and flexibility to different object's size, mass and to different starting conditions.
AB - Cooperative transport in swarm robotics is particularly challenging because the group coordination needs to be generated without using centralized control, global information and any form of direct communication. This study investigates a simple scenario for cooperative object transport in robotics swarm. The aim is to investigate the effects of torque sensors on generating effective group transport strategies for a robot swarm. The torque sensor is simulated by reading the torque feedback from Bullet physical engine hinge constraint which connects every wheel to the body of the robot. In this simulated study, a group of two agents controlled by a dynamic neural network shaped by artificial evolution are required to transport an elongate cuboid object which cannot move by single agent. We examine the flexibility of best evolved controller against different classes of object mass and size. The evolved controller exhibits a re-orientation, re-position and communicating forces through the object behaviors analogous to those observed in a biological ant. In spite of task complexity, the results demonstrate a decent performance in term of adaptability and flexibility to different object's size, mass and to different starting conditions.
KW - artificial evolution
KW - cooperative object transport
KW - dynamic neural network
KW - swarm Robotics
KW - torque sensor
UR - http://www.scopus.com/inward/record.url?scp=85152192746&partnerID=8YFLogxK
U2 - 10.1109/icdsic56987.2022.10076179
DO - 10.1109/icdsic56987.2022.10076179
M3 - Conference contribution
AN - SCOPUS:85152192746
T3 - 2022 International Conference on Data Science and Intelligent Computing, ICDSIC 2022
SP - 228
EP - 233
BT - 2022 International Conference on Data Science and Intelligent Computing, ICDSIC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 International Conference on Data Science and Intelligent Computing, ICDSIC 2022
Y2 - 1 November 2022 through 2 November 2022
ER -