Robot path-planning is one of the important issues in robotic navigation. This paper presents a novel robot path-planning approach based on the associative memory using Self-Organizing Incremental Neural Networks (SOINN). By the proposed method, an environment is first autonomously divided into a set of path-fragments by junctions. Each fragment is represented by a sequence of preliminarily gen...

We present a multimodal volume-based pre-operative surgical planning system developed around the KRDL Virtual Workbench, a mirror-based Virtual Reality system for precise work with 3D data. The planning system is being developed in collaboration with the Singapore General Hospital (SGH), and is undergoing clinical evaluation at SGH and Tan Tock Seng Hospital where 16 cases have been planned. We...

This letter addresses the 3D coverage path planning (CPP) problem for terrain reconstruction of unknown obstacle rich environments. Due to sensing limitations, proposed method, called CT-CPP, performs layered scanning region collect data, where traveling sequence is optimized using concept a tree (CT) with TSP-inspired traversal strategy. The CT-CPP method validated on high-fidelity underwater ...

Abstract. Today, natural disasters have a huge impact all over the world, while GNSS plays an important role in disaster relief and rescue. However, when ground surface is severely damaged covered, satellite positioning means are denied. In addition, site conditions often very complex may require unmanned robots such as UAVs for pre-surveying. To address raised problem, we reconstructed 3D scen...

Unmanned aerial vehicles (UAVs) are extensively employed for urban image captures and the reconstruction of large-scale 3D models due to their affordability versatility. However, most commercial flight software lack support adaptive capture multi-view images. Furthermore, limited performance battery capacity a single UAV hinder efficient capturing scenes. To address these challenges, this paper...