An efficient dynamic system for real-time robot-path planning

Abstract

Abstract-This paper presents a simple yet efficient dynamic programming (DP) shortest path algorithm for real-time collision-free robot path planning applicable to situations where targets and barriers are permitted to move. The algorithm works in real time and requires no prior knowledge of target or barrier movements. In the case that the barriers are stationary, this paper proves that this algorithm always results in the robot catching the target provided it moves at greater speed than the target, and the dynamic system update frequency is sufficiently large. Like most robot path planning approaches, the environment is represented by a topologically organized map. Each grid point on the map has only local connections to its neighboring grid points from which it receives information in real-time. The information stored at each point is a current estimate of the distance to the nearest target and the neighbor from which this distance was determined. Updating the distance estimate at each grid point is done using only information gathered from the point's neighbours, that is, each point can be considered an independent processor, and the order in which grid points are updated is not determined based on global knowledge of the current distances at each point or the previous history of each point. The robot path is determined in real-time completely from information at the robot's current grid-point location. The computational effort to update each point is minimal allowing for rapid propagation of the distance information outward along the grid from target locations. In the static situation, where both targets and barriers do not move, this algorithm is a DP solution to the shortest path problem, but is restricted by lack of global knowledge. In this case, this paper proves that the dynamic system converges in a small number of iterations to a state where the minimal distance to a target is recorded at each grid point and shows that this robot path-planning algorithm can be made to always choose an optimal path. The effectiveness of the algorithm is demonstrated through a number of simulations.

An Efficient System for Nonholonomic Mobile Robot-Path Planning

“…Being different from the model in [10] where the distance propagation is omni-directional, the vectordistance of proposed model propagates in some special direction and is vector. The novel concept, which is the influence on the robot motion caused by the road surface roughness, is proposed in our model by mathematical method.…”

“…So the robot environment is discretized into M grid points, labeled by an index i . We define i B to be the point set of free spaces that are adjacent neighbor to grid point i , max d and min d to be the minimum and maximum distances between any two adjacent neighbors in the grid of free space and target respectively and ij d to be the length of minimum path joining two free spaces i and j through freespace [10]. As illustrated in Fig.2, for regular unit square grid, the adjacent neighbor set for the grid point labeled zero and max For simplicity but without losing generality, when the robot R arrives at i position at time k t (the position of the center of gravity of robot R is grid point i ), the influence on the robot motion caused by the grid point i surface roughness replaces the influence on the area which contacts with robot at time k t .…”

“…However, the path was not shortest sometimes. A. R. Wilmas proposed distance propagating dynamic system [10], which had all advantages from Yang and Meng's model. In this model, the environment is topologically organized by grid.…”

Mobile robot path planning based on adaptive bacterial foraging algorithm

“…Thus, optimal path planning for robot manipulators is always a hot spot in research fields of robotics [1]. The goal of robot path planning is to find an optimal, collisionfree trajectory between two points in a working environment composed of many obstacles.…”

Robot Path Planning Using Bacterial Foraging Algorithm

“…Thus, optimal path planning for robot manipulators is always a hot spot in research fields of robotics. 1 The goal of robot path planning is to find an optimal, collision-free trajectory between two points in a working environment composed of many obstacles. That is, the path planning approach can be applied in static, dynamic or both environments, depending on the mode in which the environment is known and given in advance.…”