Abstract
Measuring the space area of obstacles is one of the important problems in obstacle localizing fields. Most of the existing research works on the localization of obstacles focus on where the obstacles are, and few of them measure both the positions and the areas of the obstacles. In this paper, we propose a Minimum convex bounding Polygon localizing algorithm based on Visible light Tracking (MPVT) in order to rapidly and accurately locate the position and area of a 2D obstacle in the environment of sparsely-deployed sensors. MPVT first determines the initial localization light by Visible Light Tracing method (VLT). Second, it searches for the first side of the Minimum Convex Bounding Polygon (MCBP) of the obstacle. Third, MPVT calculates the subsequent other sides and the vertexes of MCBP until the next side coincides with the first side. In order to evaluate the approximation degree between the actual values and the localization values in terms of areas, positions and shapes, we propose two performance evaluation indexes, i.e., the area ratio and the ratio of equivalent radius. We conducted experiments on the influence of obstacle orientation and sparseness of sensor deployment, the accuracy comparison with the existing methods, and the time complexity. Experiment results show that MPVT can accurately locate the position and area of the obstacle in the environment of sparsely-deployed sensors with low time overhead, and is suitable for low-cost obstacle localization applications.
Highlights
With the development of society, the applications of wireless sensor networks are becoming pervasive, such as area monitoring, biological detection, home care, object tracking, etc. [1]
Aiming at the problem of obstacle localization in two-dimensional (2D) areas, this paper presents a new method named MPVT (Minimum convex bounding Polygon localizing algorithm based on Visible light Tracking)
According to the law of counter-clockwise intersecting lights and Theorem 1, the method to search the first side of Minimum Convex Bounding Polygon (MCBP) of the obstacle is as follows: Step 1: Create a matrix M1 to store the coordinates of MCBP when searching for MCBP’s side; Step 2: Traverse the elements in the first column of lineList, mark the line where Vp lies as r1, and mark the line where the other endpoint of Lp lies as r2; Step 3: Traverse each element in lineList from r1 to r2 to find the left side line of the blocking area of each viewpoint; Step 4: Traverse each left side line Lj, and use the principle of vector cross product to determine whether Lj has an intersection point with Lp
Summary
With the development of society, the applications of wireless sensor networks are becoming pervasive, such as area monitoring, biological detection, home care, object tracking, etc. [1]. In the range-based method, ultrasonic (or infrared) rangefinders and lasers are usually used to measure the distance between observation points and obstacles This method only locates the positions of obstacles, but cannot. Aiming at the problem of obstacle localization in two-dimensional (2D) areas, this paper presents a new method named MPVT (Minimum convex bounding Polygon localizing algorithm based on Visible light Tracking). It presents MPVT, a new localization algorithm and its implementation process in sensor-sparse environment It presents two indexes for localization performance evaluation, i.e., the area ratio Sr, and the ratio of equivalent radius Lr. Compared to the existing localization methods, MPVT can accurately locate the position, and the area of the obstacle in the environment of sparsely-deployed sensors while has low time overhead.
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