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Analysis and Control of Multi-swarm Robotic Crossing and Interfering Motion

Daneshmand Dizicheh, Ali | 2018

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 50607 (08)
  4. University: Sharif University of Technology
  5. Department: Mechanical Engineering
  6. Advisor(s): Alasti, Aria
  7. Abstract:
  8. A swarm robotic is made up of a number of similar robots (identical) that these robots alone do not have any potential, but they can with each other have considerable potential. In recent years, engineers have become more interested in swarm robotic. Swarm robotic allows the use of several colleague robots instead of an advanced robot that eliminates excessive complexity and expensive equipment. The purpose of this study is to provide a method for solving the crossing problem and interfering between robot swarms. In previous studies conducted at the Sharif University of Technology, the main goal was to design algorithms for the swarm behavior of a swarm robotic. In this research, the aim is to investigate and control the interfering and crossing of more than one swarm robotic in order to avoid the collision of members, deviations from the path of motion, the trapping of members of a swarm in other swarms and dissociation in the swarm. In this regard, the velocity of the swarm and crossing the passage in a non-centered control mode were increased by providing algorithms. The algorithm is such that robots can detect the direction of swarm motion. Also, things like aggregation behavior (the aggregation of robots of a swarm in a certain range of the environment), the follower/leader mode (only one of the robots is aware of the target point, which is called leader robot, and the rest of the robot move behind the leader who is called followers) and then dimensioning to members are examined. Hence, the method of artificial potential functions was used to achieve this goal. By move in reverse direction of the potential functions and minimizing these functions, the expected target of the swarm is achieved. The potential functions have a high ability to keep robots close together, and also allow control swarm with a large number of robots. This goal was achieved by combining simultaneously or sequentially with the attraction/repulsion of the aggregation, the consensus, the swarm motion, the follower/the leader and the avoidance of stationary and moving obstacles. This method has been studied and simulated on different models. Finally, the investigation and efficiency of the obtained algorithms have been studied
  9. Keywords:
  10. Swarm Control ; Artifical Potential Functions ; Robotic Swarm ; Interfering Motion ; Crossing Motion ; Follower/Leader State

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