Square grids are commonly used in robotics and game development as spatial models and well known in AI community heuristic search algorithms (such as A*, JPS, Theta* etc.) are widely used for path planning on grids. A lot of research is concentrated on finding the shortest (in geometrical sense) paths while in many applications finding smooth paths (rather than the shortest ones but containing ...

Grids with blocked and unblocked cells are often used to represent terrain in computer games and robotics. However, paths formed by grid edges can be sub-optimal and unrealistic looking, since the possible headings are artificially constrained. We present Theta*, a variant of A*, that propagates information along grid edges without constraining the paths to grid edges. Theta* is simple, fast an...

In this paper, the problem of path planning for active simultaneous localization and mapping (SLAM) is addressed. In order to improve its localization accuracy while autonomously exploring an unknown environment the robot needs to revisit positions seen before. To that end, we propose a path planning algorithm for active SLAM that continuously improves robot’s localization while moving smoothly...

In order to make the network model was more fitting the actual condition of city traffic, this paper presents a dynamic transportation network model based on the traffic time division, and designs improved Dijkstra algorithm to solve the city traffic paths planning problem. Dijkstra algorithm is a typical singlesource shortest path algorithm is used to calculate a node to all other nodes in the...

The path planning problem is relevant for all applications in which a mobil robot should autonomously navigate. Finding the shortest path in an environment that is only partialy known and changing is a difficult problem. Replaning the entire path when the robot encounters new obstacles is computational inefficient. Starting with an initial path and than modify the path locally does not guarante...

Various forms of shortest path planning (SPP) have been studied by numerous researchers. Although SPP is generally regarded as a solved problem in 2D space, few of the existing 2D solutions can be applied to 3D. Since many real-world applications are based on 3D or higher space, this deficiency severely limits the applicability of 2D solutions. In this paper, we present a new method of partitio...

In this paper we have proposed the implementation of optimized path. We are residing on a geographical area and there is no road. So path planning is a key factor to find out the optimized path to travel to destination. This paper describes a novel approach of autonomous navigation for outdoor vehicles which includes terrain mapping, obstacle detection and avoidance, and goal seeking in cross-c...

This paper proposes a hybrid path planning algorithm incorporating a global and local search mechanism for mobile robot. The global path planning is based on Voronoi graph to establish a backbone path for the map with significantly reduced nodes for the original grid map. With the use of the backbone path, the D* algorithm is adopted to determine a shortest path between the starting and end poi...

Heuristic search methods promise to find shortest paths for path-planning problems faster than uninformed search methods. Incremental search methods, on the other hand, promise to find shortest paths for series of similar path-planning problems faster than is possible by solving each path-planning problem from scratch. In this article, we develop Lifelong Planning A* (LPA*), an incremental vers...

Understanding how and how far information, behaviors, or pathogens spread in social networks is an important problem, having implications for both predicting the size of epidemics, as well as for planning effective interventions. There are, however, two main challenges for inferring spreading paths in real-world networks. One is the practical difficulty of observing a dynamic process on a netwo...