Collision-free local planner for unknown subterranean navigation

When operating in confined spaces or near obstacles, collision-free path planning is an essential requirement for autonomous exploration in unknown environments. This study presents an autonomous exploration technique using a carefully designed collision-free local planner. Using LiDAR range measurements, a local end-point selection method is designed, and the path is generated from the current position to the selected end-point. The generated path showed the consistent collision-free path in real-time by adopting the Euclidean signed distance field-based grid-search method. The results consistently demonstrated the safety and reliability of the proposed path-planning method. Real-world experiments are conducted in three different mines, demonstrating successful autonomous exploration flights in environment with various structural conditions. The results showed the high capability of the proposed flight autonomy framework for lightweight aerial robot systems. In addition, our drone performed an autonomous mission in the tunnel circuit competition (Phase 1) of the DARPA Subterranean Challenge.     

无金属卟啉置换辣根过氧化物酶辅基研究

不同结构的卟啉插入去辅基辣根过氧化物酶(apo-HRP)所得重构酶具有类过氧化物酶的催化活性.采用紫外分光光度法和荧光光度法对这些重构酶进行研究.结果表明TPyP-apo-HRP比其他卟啉类插入重构蛋白具有的类过氧化物酶催化活性高.