Map Building of Unknown Environment Using L1-norm, Point-to-Point Metric and Evolutionary Computation

Polibits ◽  
2012 ◽  
Vol 46 ◽  
pp. 29-38
Author(s):  
Jaroslav Moravec
Keyword(s):  
Evolutionary Computation ◽  
Map Building ◽  
L1 Norm ◽  
Unknown Environment ◽  
Point To Point

scholarly journals Polar Metric-Weighted Norm-Based Scan Matching for Robot Pose Estimation

2016 ◽  
Vol 2016 ◽  
pp. 1-20
Author(s):  
Guanglei Huo ◽  
Lijun Zhao ◽  
Ke Wang ◽  
Ruifeng Li ◽  
Jianqiang Li
Keyword(s):  
Pose Estimation ◽  
Value Function ◽  
Rotation Angle ◽  
Accurate Estimation ◽  
Weighted Norm ◽  
Map Building ◽  
Scan Matching ◽  
Constant Weight ◽  
Absolute Value ◽  
Point To Point

A novel point-to-point scan matching approach is proposed to address pose estimation and map building issues of mobile robots. Polar Scan Matching (PSM) and Metric-Based Iterative Closest Point (Mb-ICP) are usually employed for point-to-point scan matching tasks. However, due to the facts that PSM considers the distribution similarity of polar radii in irrelevant region of reference and current scans and Mb-ICP assumes a constant weight in the norm about rotation angle, they may lead to a mismatching of the reference and current scan in real-world scenarios. In order to obtain better match results and accurate estimation of the robot pose, we introduce a new metric rule, Polar Metric-Weighted Norm (PMWN), which takes both rotation and translation into account to match the reference and current scan. For robot pose estimation, the heading rotation angle is estimated by correspondences establishing results and further corrected by an absolute-value function, and then the geometric property of PMWN called projected circle is used to estimate the robot translation. The extensive experiments are conducted to evaluate the performance of PMWN-based approach. The results show that the proposed approach outperforms PSM and Mb-ICP in terms of accuracy, efficiency, and loop closure error of mapping.

scholarly journals Growing Neural Gas Based Topological Environmental Map Building and Path Planning in Unknown Environment

2021 ◽  
Vol 33 (4) ◽  
pp. 872-884
Author(s):  
Yuichiro TODA ◽  
Hikari MIYASE ◽  
Mutsumi IWASA ◽  
Akimasa WADA ◽  
Soma TAKEDA ◽  
...  
Keyword(s):  
Path Planning ◽  
Map Building ◽  
Growing Neural Gas ◽  
Unknown Environment ◽  
Neural Gas ◽  
Environmental Map

Map Building of Indoor Unknown Environment Based on Robot Service Mission Direction

ROBOT ◽  
2010 ◽  
Vol 32 (2) ◽  
pp. 196-203 ◽  
Author(s):  
Hao WU ◽  
Guohui TIAN ◽  
Xibo CHEN ◽  
Taotao ZHANG ◽  
Fengyu ZHOU
Keyword(s):  
Map Building ◽  
Unknown Environment ◽  
Service Mission

Create Terrain Maps for Unmanned Ground Platform

2013 ◽  
Vol 210 ◽  
pp. 32-39
Author(s):  
Andrzej Typiak ◽  
Michał Gnatowski ◽  
Jacek Szklarski
Keyword(s):  
Map Building ◽  
Insufficient Information ◽  
Unknown Environment ◽  
Combining Information

A typical unmanned and remotely operated platform is usually equipped with cameras which give insufficient information about the nearest environment and an operator has difficulties in driving such a platform in unknown environment. In this paper, a problem of the platform nearest area map building based on additional devices is considered. The platform is equipped with SICK LMS lasers, inclinometer and radars. Combining information from the devices allows to build a map which helps an operator to drive the platform more efficiently.

Antisway Control for a Rotary Crane by Using Evolutionary Computation

2016 ◽  
Vol 28 (5) ◽  
pp. 646-653 ◽  
Author(s):  
Akira Abe ◽  
◽  
Keisuke Okabe ◽  
Keyword(s):  
Evolutionary Computation ◽  
Optimal Trajectory ◽  
Control Method ◽  
Open Loop ◽  
Two Dimensional ◽  
Loop Control ◽  
Dimensional Plane ◽  
Rotary Crane ◽  
Point To Point ◽  
Sway Motion

[abstFig src='/00280005/05.jpg' width='250' text='Photograph of the experimental setup' ] We present a simple antisway control method for a rotary crane, whose load can move in a two-dimensional plane. In particular, we investigate the suppression of residual sway motion of a rotary crane with a boom that performs point-to-point motion. In the proposed method, we attempt to generate the trajectory of the boom using a combination of polynomial and cycloidal functions. The profile of the generated trajectory depends on the coefficients of the polynomial function. Thus, it is necessary to tune the coefficients to minimize the sway motion in the two-dimensional plane as much as possible. We adopt a particle swarm optimization algorithm, an evolutionary computation technique, to tune the coefficients and then obtain the optimal trajectory. By rotating the boom along the optimal trajectory, the two-dimensional residual sway motion is suppressed, i.e., an open-loop control is realized. The effectiveness and feasibility of the proposed control scheme is demonstrated via simulations and experiments.

scholarly journals Obstacle Avoidance for Unmanned Undersea Vehicle in Unknown Unstructured Environment

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Zheping Yan ◽  
Yufei Zhao ◽  
Shuping Hou ◽  
Honghan Zhang ◽  
Yalin Zheng
Keyword(s):  
Vector Field ◽  
Obstacle Avoidance ◽  
Local Environment ◽  
High Accuracy ◽  
Map Building ◽  
Unknown Environment ◽  
Obstacle Avoiding ◽  
Unstructured Environment ◽  
Occupancy Grids ◽  
Undersea Vehicle

To avoid obstacle in the unknown environment for unmanned undersea vehicle (UUV), an obstacle avoiding system based on improved vector field histogram (VFH) is designed. Forward looking sonar is used to detect the environment, and the divisional sonar modal is applied to deal with the measure uncertainty. To adapt to the VFH, rolling occupancy grids are used for the map building, and high accuracy details of local environment are obtained. The threshold is adaptively adjusted by the statistic of obstacles to solve the problem that VFH is sensitive to threshold. To improve the environment adaptability, the hybrid-behaviors strategy is proposed, which selects the optimal avoidance command according to the motion status and environment character. The simulation shows that UUV could avoid the obstacles fast and escape from the U shape obstacles.

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