1. This article discusses the use of heuristic methods to solve the problem of task allocation and collision-free path planning for a centralized multi-robots system used for industrial plant inspection.
2. The article reviews existing literature on multi-robots systems and their applications, such as hazardous waste cleanup, box pushing, object transportation, exploration of unknown environments, and task assignment in static environments.
3. The article proposes an algorithm combining genetic algorithms (GA) and A* algorithm to solve the task allocation and path planning problems for multiple robots working in a common workspace.
The article is generally reliable and trustworthy. It provides a comprehensive review of existing literature on multi-robots systems and their applications, which helps to provide context for the proposed algorithm. The authors also provide a detailed explanation of the proposed algorithm, which is based on two heuristic methods - genetic algorithms (GA) and A* algorithm - that are well established in robotics research. Furthermore, the authors discuss potential issues with their approach such as time delays caused by collision avoidance sensors, controllers, and motion planners.
However, there are some points that could be improved upon in terms of trustworthiness and reliability. For example, while the authors do mention potential risks associated with their approach (e.g., time delays), they do not provide any evidence or data to support this claim or explore possible counterarguments or solutions to mitigate these risks. Additionally, while the authors do discuss potential biases in existing literature on multi-robots systems (e.g., one-sided reporting), they do not provide any evidence or data to support this claim either nor do they explore possible counterarguments or solutions to address these biases. Finally, it would have been beneficial if the authors had provided more detail about how their proposed algorithm works in practice (e.g., what types of tasks can it handle).