This research casts the problem of exploration into one of collecting information and enables the completion of complex exploration tasks by considering multiple sources of information. This paper describes a methodology to solve exploration tasks which computes the expected information gain, for each information source, from a sensor reading. It also proposes a greedy search algorithm to colle...

Autonomous off-road navigation of robotic ground vehicles has important applications on Earth and in space exploration. Progress in this domain has been retarded by the limited lookahead range of 3-D sensors and by the difficulty of preprogramming systems to understand the traversability of the wide variety of terrain they can encounter. Enabling robots to learn from experience may alleviate bo...

Post-earthquake road traversability is a critical factor that affects traffic conditions. Therefore, post-earthquake simulation method considering was proposed in this study. First, the impact ranges of earthquake-induced building collapse and fire spread buildings were analyzed, determined accordingly. Subsequently, flow predicted based on characteristics, micro-level vehicle behaviors simulat...

This paper presents an approach to mobile robot path planning using case-based reasoning together with map-based path planning. The map-based path planner is used to seed the case-base with innovative solutions. The casebase stores the paths and the information about their traversability. While planning the route those paths are preferred that according to the former experience are least risky.

Estimating the traversability of terrain should be reliable and accurate in diverse conditions for autonomous driving off-road environments. However, learning-based approaches often yield unreliable results when confronted with unfamiliar contexts, it is challenging to obtain manual annotations frequently new circumstances. In this paper, we introduce a method learning from images that utilizes...

In this letter, a new method of path planning for unmanned ground vehicles (UGVs) on terrain is developed. For UGVs moving terrain, traversability and collision avoidance are important factors. If not considered, the planned may lead UGV into areas that will cause rough vehicle motion or to getting stuck if low. The proposed based Hybrid A* algorithm uses estimated find optimizes both distance ...