There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

Abstract In this paper, a new technique for multi-robot localization in an unknown environment, called the leader-follower localization algorithm is presented. The framework utilized here is one robot that goes about as a leader and different robots are considered as followers distributed randomly in the environment. Every robot equipped with RP lidar sensors to scan the environment and gather information about every robot. This information utilized by the leader to distinguish and confine every robot in the environment. The issue of not noticeable robots is solved by contrasting their distances with the leader. Moreover, the equivalent distance robot issue is unraveled by utilizing the permutation algorithm. Several simulation scenarios with different positions and orientations are implemented on (37) robots to show the performance of the introduced technique.

RP Lidar Sensor for Multi-Robot Localization using Leader Follower Algorithm

Autonomous robot swarm systems allow to address many inherent limitations of single robot systems, such as scalability and reliability. As a consequence, these have found their way into numerous applications including in the space and aerospace domains like swarm-based asteroid observation or counter-drone systems. However, achieving stable formations around a point of interest using different number of robots and diverse initial conditions can be challenging. In this article we propose a novel method for autonomous robots swarms self-organisation solely relying on their relative position (angle and distance). This work focuses on an evolutionary optimisation approach to calculate the parameters of the swarm, e.g. inter-robot distance, to achieve a reliable formation under different initial conditions. Experiments are conducted using realistic simulations and considering four case studies. The results observed after testing the optimal configurations on 72 unseen scenarios per case study showed the high robustness of our proposal since the desired formation was always achieved. The ability of self-organise around a point of interest maintaining a predefined fixed distance was also validated using real robots.

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Optimising autonomous robot swarm parameters for stable formation design

This paper mainly studies the motion consensus and formation control of robot swarm, and designs a new formation control and trajectory tracking algorithm based on artificial potential field method and implicit leaders. The algorithm can control the swarm to approach the desired formation and realize collision avoidance between robots. By "implicitly" integrating the leaders into the swarm, the proposed algorithm can not only guarantee a swarm of robots to move along predefined formation and track scheduled trajectory with certain velocity, dynamic leader reassignment is also realized, thus enhancing the adaptability and expansibility of the swarm. Numerical simulation results verify the correctness of the theoretical analysis and the effectiveness of the algorithm.

Formation control of robot swarm with implicit leaders

This paper denotes a survey on formation control of multi-mobile robot systems which drawn significant attention for the last years. It is concentrated on the stability of multi mobile robots when they obtained the required formation. Also this paper discusses the approaches of formation control and applications of them in changing and remote environments. Two classifications for the formation control methods are surveyed in this paper: the formation control strategies and the formation control stability. The differences among the surveyed approaches are discussed and the results are summarized.

/pdf/a-survey-of-multi-mobile-robot-formation-control-4v5galht7t.pdf

A Bayadir

Papers

A Survey of Multi-mobile Robot Formation Control