Swarm robotic systems are mainly inspired by swarms of socials insects and the collective emergent behavior that arises from their cooperation at the lower lever. Despite the limited sensory ability, computational power, and communication means of each swarm member, the swarm as a group manages to achieve difficult tasks such as searching for food in terrains with obstacles that individual robots cannot achieve in isolation of the other group members. Moreover, such tasks are usually achieved without having information sharing capabilities at the swarm level or having a centralized decision making system. In this report, I survey the state of the field of applying adaptive control method to increase swarm robotic systems robustness to the failure of individual robots, and increase its efficiency in performing its task. A few techniques for the division of labor problem are briefly presented while one of them is given in more detail. A discussion of the advantages and disadvantages of this system is given and suggestions of potential improvements that can be made to the system are presented.
Mixed Reality Environment and High-Dimensional Continuification Control for Swarm Robotics
Scuola Superiore Meridionale（南方高等学院）；University of Rome La Sapienza（罗马第一大学）；Tandon School of Engineering, New York University（纽约大学坦登工程学院）；University of Naples Federico II（那不勒斯费德里科二世大学）
UC Berkeley（加州大学伯克利分校）；UC San Diego（加州大学圣地亚哥分校）；Cornell University（康奈尔大学）；University of Edinburgh（爱丁堡大学）；Institute for Advanced Study（普林斯顿高等研究院）；Cal Poly（加州州立理工大学波莫纳分校）；UCLA（加州大学洛杉矶分校）
Design of a Formation Control System to Assist Human Operators in Flying a Swarm of Robotic Blimps
Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology（香港科技大学电子与计算机工程系）；School of Software Engineering, Beijing Jiaotong University（北京交通大学软件学院）；Department of Electronic Engineering, Sunchon National University（全州国立大学电子工程系）；Department of Computer Science, Emory University（埃默里大学计算机科学系）
SwarmGPT: Combining Large Language Models with Safe Motion Planning for Drone Swarm Choreography
Learning Systems and Robotics Lab（学习系统与机器人实验室）；Munich Institute of Robotics and Machine Intelligence（慕尼黑机器人与机器智能研究所）；Technical University of Munich（慕尼黑技术大学）
Navigating Robot Swarm Through a Virtual Tube with Flow-Adaptive Distribution Control
School of Mathematical Sciences, Beihang University（北京航空航天大学数学科学学院）；School of Automation Science and Electrical Engineering, Beihang University（北京航空航天大学自动化科学与电气工程学院）
