Swarm Robotics Algorithms
Advanced Robotics Special Issue Call for Papers
Deadline: 29 February 2020
Swarm robotics is defined as a group of coordinated robots acting as a single system. Each swarm comprises of many simple small sized physical robots. These robots are used to accomplish a task through collective behavior and coordinated interactions and communications among them. In other words the nature of smart robotics is distributed and decentralized. The basic essence of swarm robotics is divide and conquer approach where in several simple robots are deployed and the complex task is broken into smaller activities and assigned to individual robots. Swarm robotics is governed by certain characteristics. Each robot in the swarm must be autonomous in nature. They must be self sensory and actuate in real time environment. A swarm should typically contain many simple robots. All the simple robots in the swarm must be homogeneous in nature. These simple robots in the swarm must be highly collaborative and communicative with each other. Swarm robotics has been deployed across several applications that involve tasks such as miniaturization and distributed sensing. Some of the real time applications of swarm robotics are disaster recovery missions, intrusion detection, bomb threat detection, agriculture foraging, defense applications, micro air vehicles and motion capturing.
Typical advantages of swarm robotics are enhanced performance by decomposing the task there by leveraging the principle of parallelism, task enablement by group of robots accomplishing a task which cannot be performed using a single robot, distributed sensing which means that scope and geography covered by swarm robots is generally wider than that of a single robot, distributed action referring to swarm robots performing autonomous tasks independently at different places, fault tolerance enabled by the physical presence of multiple simple robots present in the swarm so that a faulty robot can be replaced by another without impacting the outcome of the task. Like other technologies, swarm robotics also has its own set of disadvantages. Swarm robots are prone to collisions due to occlusion and interference. There are possibilities of some uncertainty to persist between individual robots in the swarm while communicating with each other. Also the overall system cost of deploying a swarm robotics enabled system is pretty high. These challenges provide opportunities to explore the possibilities of new algorithms and techniques that enable better development, maintenance and deployment of swarm robotic systems.
This special issue on “Swarm robotics algorithms” provides an excellent platform for core researchers and robotic enthusiasts to share novel ideas, new algorithms and approaches, efficient enhancements, innovative applications and many more new works in the field of swarm robotics. Topics of interest include but are not restricted to:
- Advanced dynamic task allocation algorithms in swarm robotics.
- Smart algorithms to enhance parallelism in swarm robotics.
- Robot localization and control algorithms in swarm robotics.
- Algorithms to enhance Swarm robotic control.
- Pattern formation techniques and algorithms in swarm robotics.
- Robot task scheduling algorithms in swarm robotics.
- Algorithms and techniques to enhance inter robot communication in swarm robotics.
- Smart algorithms for robot positioning in swarm robotics.
- Swarm robotics based gaming algorithms.
- Algorithms for collective movements of swarm robots.
- Smart algorithms that enable coupling and decoupling of robots in swarm robotics.
- Smart aggregation algorithms in swarm robotics.
- Algorithms for Swarm robotics and its use in defense applications.
- Algorithms for Swarm robotics and its use in satellite communication.
- Algorithms for Swarm robotics and its use in unmanned missions.
- Algorithms to address occlusion problems in swarm robotics.
- Algorithms to address interference problems in swarm robotics.
- Distributed action management algorithms in swarm robotics.
- Capacity management algorithms in swarm robotics.
- Collective behavioral analysis and algorithms that aid swarm robotics.
- Novel applications and algorithms using swarm robotics.
- Swarm robotic algorithms for collective object transportation and movement.
- Real time applications and algorithms in swarm robotics.
- Collective task mapping algorithms that aid swarm robotics.
The full-length manuscript (either PDF file or MS word file) should be sent by February 29, 2020 to the office of Advanced Robotics, the Robotics Society of Japan through the website of Advanced Robotics (http://www.rsj.or.jp/ar/submission). Instructions for authors and example manuscript template are available on the website, too. When submitting please also send a copy of your submission to Dr.-Ing. Heiko Hamann (email@example.com) for confirmation.
Dr.-Ing. Heiko Hamann (University of Lübeck)
Dr.-Ing. Mladen Berekovic (University of Lübeck)
Dr. Norbert Stoll (University of Rostock)
Dr. Yancheng Ji (Nantong University)
Dr. Bharat S. Rawal Kshatriya (IST)
Published on 8th July. Last updated on 8th July.