Advanced Multi-Robot Path Planning and Control Architecture for Precision Cancer Treatment Systems

Abstract

This article presents an innovative approach to mobile robot path planning and control systems specifically designed for cancer detection and treatment applications in medical environments. This article introduces a novel prioritized path-planning algorithm that enables multiple robots to navigate collision-free while maintaining precise coordination during medical procedures. The system architecture integrates advanced technologies, including ATL COM/VC++ components, digital/analog interfacing, and COM/.NET interoperable objects with C# user controls and XML for comprehensive machine management. This article incorporates fuzzy logic and machine learning techniques for intelligent collision avoidance, alongside artificial neural networks and generative AI models for pattern classification and forecasting. The implementation leverages multiple communication protocols, including TCP/IP, RS232, CAN, and USB, to ensure robust connectivity across all system components. Extensive testing through black/white box methodologies, regression testing, and simulation of pneumatic, hydraulic, and PLC components demonstrates the system's reliability and precision. This article shows significant improvements in path planning efficiency, control system response times, and overall system reliability compared to existing solutions. This article suggests that this integrated approach not only enhances the accuracy of cancer detection and treatment procedures but also provides a scalable framework for future medical robotics applications. The system's successful validation in clinical settings indicates its potential for widespread adoption in medical facilities, marking a substantial advancement in automated medical robotics.