Research on Path Planning Method of Coal Mine Robot to Avoid Obstacle in Gas Distribution Area

Abstract

As the explosion-proof safety level of a coal mine robot has not yet reached the level of intrinsic safety “ia” and it cannot work in a dangerous gas distribution area, therefore, path planning methods for coal mine robot to avoid the dangerous area of gas are necessary. In this paper, to avoid a secondary explosion when the coal mine robot passes through gas hazard zones, a path planning method is proposed with consideration of gas concentration distributions. First, with consideration of gas distribution area and obstacles, MAKLINK method is adopted to describe the working environment network diagram of the coal mine robot. Second, the initial working paths for the coal mine robot are obtained based on Dijkstra algorithm, and then the global optimal working path for the coal mine robot is obtained based on ant colony algorithm. Lastly, experiments are conducted in a roadway after an accident, and results by different path planning methods are compared, which verified the effectiveness of the proposed path planning method.

Design and development of a novel autonomous scaled multiwheeled vehicle

“…Within each region, three different positions and orientations are randomly selected as starting poses. From there, all poses are sent to the parking area via Dijkstra's and TEB algorithm to account for any obstacles along the way [41,42]. To ensure a proper reset of error, sensor power is cycled between tests.…”

Forecast of Gas Distribution Area for Coal Mine Robot

“…In formula (3). 1 2 , ,..., n m m m are input parameters, 1 m is output parameter of system, and 1 2 , , ,..., n a b b b are the coefficients of the differential equation.…”

“…If the method of measuring gas concentration while walking is adopted, that not only decreases the efficiency of the coal mine robot, but also consumes a lot of energy and time, this is not feasible for coal mine robot powered by batteries. Many scholars at home and abroad had done much in the prediction of gas concentration, mainly in comparing predicted model [1] , improvement of prediction model [2],effective prediction methods or algorithms [3,4], combination forecasting model, [5,6] and so on. However, these studies mostly focused on forecasting methods and modeling, the data used is usually obtained from a place for a long period of time, or some key sampling-points data in mining face ,fully mechanized coal face or excavation roadway, and the sensor is also used for a fixed installation of a single sensor, Very few people obtained the gas data by continuously measuring an area, notwithstanding the gas in coal mine obeys regional distribution and migration law [3], the environment in coal mine is always very complex, there are many factors influence gas concentration and gas distribution area, so it is meaningful and valuable to predict the gas concentration and gas distribution in a short period.…”

A Novel Edge Detection Algorithm for Mobile Robot Path Planning

“…Also, most of them solved the optimal path in terms of single objective. In [24], the initial working path for the robot is obtained by using Dijkstra algorithm. Then ant colony algorithm is adopted to optimize this initial path and the global optimal path is obtained.…”