An efficient algorithm for the euclidean distance transformation

1996 ◽  
Vol 27 (7) ◽  
pp. 18-24 ◽  
Author(s):  
Toshihiro Kato ◽  
Tomio Hirata ◽  
Toyofumi Saito ◽  
Kenji Kise
Keyword(s):  
Efficient Algorithm ◽  
Euclidean Distance ◽  
Distance Transformation

scholarly journals Trajectory Tracking For Quadrotors: An Optimization-Based Planning Followed By Controlling Approach

2021 ◽  
Author(s):  
Geesara Kulathunga ◽  
Dmitry Devitt ◽  
Alexandr Klimchik
Keyword(s):  
Trajectory Tracking ◽  
Euclidean Distance ◽  
Control Policy ◽  
Multiple Shooting ◽  
Reference Trajectory ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Distance Transformation ◽  
Direct Collocation ◽  
Better Than

Abstract We present an optimization-based reference trajectory tracking method for quadrotor robots for slow-speed maneuvers. The proposed method uses planning followed by the controlling paradigm. The basic concept of the proposed method is an analogy to Linear Quadratic Gaussian (LQG) in which Nonlinear Model Predictive Control (NMPC) is employed for predicting optimal control policy in each iteration. Multiple-shooting (MS) is suggested over Direct-collocation (DC) for imposing constraints when modelling the NMPC. Incremental Euclidean Distance Transformation Map (EDTM) is constructed for obtaining the closest free distances relative to the predicted trajectory; these distances are considered obstacle constraints. The reference trajectory is generated, ensuring dynamic feasibility. The objective is to minimize the error between the quadrotor’s current pose and the desired reference trajectory pose in each iteration. Finally, we evaluated the proposed method with two other approaches and showed that our proposal is better than those two in terms of reaching the goal without any collision. Additionally, we published a new dataset, which can be used for evaluating the performance of trajectory tracking algorithms.

scholarly journals An Efficient Algorithm for Maximizing Range Sum Queries in a Road Network

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Tien-Khoi Phan ◽  
HaRim Jung ◽  
Ung-Mo Kim
Keyword(s):  
Efficient Algorithm ◽  
Road Network ◽  
Euclidean Distance ◽  
Optimal Location ◽  
External Memory ◽  
Distance Metric ◽  
Network Database ◽  
Road Network Database

Given a set of positive-weighted points and a query rectangler(specified by a client) of given extents, the goal of a maximizing range sum (MaxRS) query is to find the optimal location ofrsuch that the total weights of all the points covered byrare maximized. All existing methods for processing MaxRS queries assume the Euclidean distance metric. In many location-based applications, however, the motion of a client may be constrained by an underlying (spatial) road network; that is, the client cannot move freely in space. This paper addresses the problem of processing MaxRS queries in a road network. We propose the external-memory algorithm that is suited for a large road network database. In addition, in contrast to the existing methods, which retrieve only one optimal location, our proposed algorithm retrieves all the possible optimal locations. Through simulations, we evaluate the performance of the proposed algorithm.

scholarly journals A unified framework for isotropic meshing based on narrow-band Euclidean distance transformation

2015 ◽  
Vol 1 (3) ◽  
pp. 239-251 ◽  
Author(s):  
Yuen-Shan Leung ◽  
Xiaoning Wang ◽  
Ying He ◽  
Yong-Jin Liu ◽  
Charlie C. L. Wang
Keyword(s):  
Euclidean Distance ◽  
Narrow Band ◽  
Unified Framework ◽  
Distance Transformation
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