In the current era of the industrial revolution, mobile robots are playing a pivotal role in helping out mankind in many complex and hazardous environments for performing tasks like search and rescue, obstacle avoidance, mining and security surveillance, etc. A lot of navigation algorithms have been developed in recent years but novel challenges still exist in autonomous path planning of multiple robots to track and follow multiple intruders. This report demonstrates a decentralized strategy of arithmetic mean based navigation algorithm for a group of mobile robots to navigate through an unknown environment filled with obstacles to detect and follow multiple invading intruders. The suggested navigation strategy ensures that mobile robots safely move right in the middle of surrounding obstacles to maintain a safe distance and to avoid collision with obstacles and each other. The conventional method of color recognition is used to detect dynamic intruders and calculate pixel values using the Microsoft Kinect sensor camera. A probability of danger algorithm is introduced to ensure that all the intruders present in the environment are being followed by friendly robots on the bases of the minimum distance between an intruder and its follower. The mobile robots follow intruders movement on the bases of their pixel values. The low pixel value means that intruder is far away and high pixel value represents that intruder is closer to the friendly robots. All the algorithms and image processing techniques are implemented and tested in WEBOTS simulation environment using C programming language and the results show the success of proposed arithmetic mean based navigation and probability of danger based intruders following algorithms.
EGO-Swarm: A Fully Autonomous and Decentralized Quadrotor Swarm System in Cluttered Environments
Zhejiang University（浙江大学）；National Engineering Research Center for Industrial Automation (Ningbo Institute)（国家工业自动化工程技术研究中心（宁波研究院））；Huzhou Institute, Zhejiang University（浙江大学湖州研究院）
Decentralized, Self-organizing, Potential field-based Control for Individuallymotivated, Mobile Agents in a Cluttered Environment: A Vector-Harmonic Potential Field Approach
King Fahd University of Petroleum and Minerals（法赫德国王石油与矿业大学）
Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning
School of Intelligence Science and Engineering（智能科学与工程学院）；Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics（广东省智能变形机制与自适应机器人重点实验室）；Shenzhen Key Lab for Advanced Motion Control and Modern Automation Equipments（深圳先进运动控制与现代自动化设备重点实验室）；Harbin Institute of Technology（哈尔滨工业大学）
Visibility-Aware Cooperative Tracking with Decentralized LiDAR-Based Aerial Swarms
Department of Mechanical Engineering, The University of Hong Kong（香港大学机械工程系）；School of Intelligent System Engineering, Sun Yat-sen University（中山大学智能系统工程学院）
OA-ECBVC: A Cooperative Collision-free Encirclement and Capture Approach in Cluttered Environments
The Chinese University of Hong Kong（香港中文大学）；The University of Hong Kong（香港大学）；Hebei University of Science and Technology（河北科技大学）；Tongji University（同济大学）
Decentralized Simultaneous Multi-target Exploration using a Connected Network of Multiple Robots
Max Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）；CNRS（法国国家科学研究中心）；Irisa（法国国家信息与自动化研究所雷恩布列塔尼大西洋研究中心）；Inria Rennes Bretagne Atlantique（法国国家信息与自动化研究所雷恩布列塔尼大西洋研究中心）；Max Planck Institute for Biological Cybernetics（马克斯·普朗克生物控制论研究所）；LAAS（LAAS分析及系统架构实验室）；Univ de Toulouse（图卢兹大学）
Decentralized Heterogeneous Multi-Robot Collaborative Exploration for Indoor and Outdoor 3D Environments
College of Artificial Intelligence, Harbin Institute of Technology (Shenzhen)（哈尔滨工业大学（深圳）人工智能学院）；Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong（香港中文大学机械与自动化工程系）
Communication-Efficient Module-Wise Federated Learning for Grasp Pose Detection in Cluttered Environments
Department of Electronic Engineering, Hanyang University（电子工程系，翰阳大学）；Department of Computing, Gachon University（计算系，加恩大学）；Department of Artificial Intelligence, Hanyang University（人工智能系，翰阳大学）
Merry-Go-Round: Safe Control of Decentralized Multi-Robot Systems with Deadlock Prevention
Dept. of Artificial Intelligence, Sogang University（人工智能系，ソガン大学）；Dept. of Electronic Engineering, Sogang University（电子工程系，ソガン大学）；Dept. of Computer Science, University of Illinois Chicago（计算机科学系，伊利诺伊大学香槟分校）
