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Initiative Exploration and Feature Maps Building in Unkonwn Environment for Indoor Robots

Author: LiZhiPeng
Tutor: LvWeiXin
School: Harbin Institute of Technology
Course: Mechanical Engineering
Keywords: Service Robots Initiative to explore Map building Dotted line feature map Dynamic factors
CLC: TP242.3
Type: Master's thesis
Year: 2011
Downloads: 52
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Abstract

With the continuous development of modern science and technology, service robots have begun to gradually into the home independently explore an unknown environment and build a map is one of the basic functions of the service robot, so inevitably become a hot research service robot autonomy sex the first step. Oriented indoor unknown complex environment, this paper mainly for the following work: one for indoor service robot build a map in the rapidly expanding random tree (RRT) path planning algorithm based on the proposed initiative to explore; indoor environment, point line feature map under the framework of feature extraction methods improved, a new angle feature extraction methods; extraction of dynamic factors in the environment, an active exploration and mapping system was constructed of the actual trial the problem analysis and solution. Firstly, from three angles of the robot's motion model and sensor model and the model of the odometer of the service robot platform is analyzed from the perspective of the actual application must be noted that in the latter part of the work described. RRT application of the limitations of known static environment, in order to avoid the blindness of exploration, the RRT boundary heuristic path planning combined into the bracketing search ideology, and added a dynamic factor in obstacle avoidance strategy, proposed a suitable for indoor service the robot build map exploration HSRRT, and its feasibility is verified by simulation. Point line feature map framework for angle feature point extraction of difficult problems, gradually dichotomy; line extraction process integrate into the Ransac of algorithms to ensure the accuracy of the linear features; finite difference dynamic factors extract; final map optimization reduces storage space, a complete map of the build system. Experimental validation algorithm HSRRT feasibility Matlab simulation experiments; verify the step-by-step practical dichotomy in terms of map building, and by comparison with the three-point prediction method proved its high accuracy and repeatability; by adding RANSAC fitting a straight line before and after the experimental comparison to prove the accuracy of the present method. Odometer correction MbICP algorithm slipping relative error caused by the impact, proved by the experiment, and propose a method for cumulative error correction odometer method used to construct a more accurate map; proved by experiments on dynamic factors processing, exploration of its obstacle avoidance exclude build the map.

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