Virtual Structure Based Formation Tracking of Multiple Wheeled Mobile Robots: An Optimization Perspective

Today, with the increasing development of science and technology, many systems need to be optimized to find the optimal solution of the system. this kind of problem is also called optimization problem. Especially in the formation problem of multi-wheeled mobile robots, the optimization algorithm can help us to find the optimal solution of the formation problem. In this paper, the formation problem of multi-wheeled mobile robots is studied from the point of view of optimization. In order to reduce the complexity of the formation problem, we first put the robots with the same requirements into a group. Then, by using the virtual structure method, the formation problem is reduced to a virtual WMR trajectory tracking problem with placeholders, which describes the expected position of each WMR formation. By using placeholders, you can get the desired track for each WMR. In addition, in order to avoid the collision between multiple WMR in the group, we add an attraction to the trajectory tracking method. Because MWMR in the same team have different attractions, collisions can be easily avoided. Through simulation analysis, it is proved that the optimization model is reasonable and correct. In the last part, the limitations of this model and corresponding suggestions are given

Neural Network Algorithm for Complete Coverage Path Planning in Industrial Robotic Platforms: A Simulation-Based Study

This thesis discusses complete coverage path planning (CPP) algorithms used for robotic systems in dynamic and changing environments. The focus is on the Neural Network algorithm [9] and its adaptation for practical use on an industrial-ready robotic platform. Various approaches to CPP are described, including offline and online algorithms, and a structured approach using grid mapping-based methods. The thesis also mentions the physical implementation of the algorithm on a multi-robotic system and discusses the limitations of current methods for industrial applications. The objective of the research is to develop a system for complete coverage path planning with higher coverage completeness, lower path repetition rate, and less path execution time. The research is limited to real-world simulations using Gazebo World and Robot Operating System (ROS)