Online Multi-agent SLAM

Welcome to MASL (Multi-Agent Systems Lab), where we specialize in robotics and autonomous systems. Our research focuses on pioneering SLAM path planning and navigation for multi-agent systems, redefining interactions with technology in dynamic environments. Join us as we push the boundaries of scientific innovation and practical application.
In this video, our innovation is a refined TSD-based SLAM algorithm, tailored for high-stakes rescue operations using multi-agent online SLAM systems. By integrating the General Iterative Closest Point (GICP) method, we enhance our mapping precision, swiftly adapting to new challenges in real-world scenarios. This technology produces exact two-dimensional maps crucial for navigating through complex, debris-laden terrains.
We incorporate advanced sensory technologies like LiDAR and IMUs into smart helmets, boosting the safety and efficiency of rescue missions. Our experiments have shown these enhancements not only improve map accuracy but also the effectiveness of online map merging, enabling quicker and more accurate navigation in hazardous environments.

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For more details on our innovative projects and research in multi-agent systems, visit our website at masl.kumoh.ac.kr.