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Soonyong Park,Soohwan Kim,Sung-Kee Park 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10
This paper presents a novel vision-based global localization approach that uses an object and spatial layout based hybrid map. We model any indoor environments using the following visual cues with a stereo camera; local invariant features for object recognition and their 3D positions for object pose estimation. Also, we use the depth information at the horizontal centerline in images where the optical axis passes through, which is similar to the data of a 2D laser range finder. Therefore, we can build a hybrid local node for a topological map that is composed of a metric map and an object location map. Based on such modeling, we suggest a coarse-to-fine strategy for the global localization. The coarse pose is obtained by means of object recognition and a least-squares fitting, and then its fine pose is estimated with a particle filtering algorithm. With real experiments, we show that our proposed method can be an effective vision-based global localization algorithm.
Fast and Scalable Approximate Spectral Matching for Higher Order Graph Matching
Soonyong Park,Sung-Kee Park,Hebert, Martial IEEE 2014 IEEE transactions on pattern analysis and machine Vol.36 No.3
<P>This paper presents a fast and efficient computational approach to higher order spectral graph matching. Exploiting the redundancy in a tensor representing the affinity between feature points, we approximate the affinity tensor with the linear combination of Kronecker products between bases and index tensors. The bases and index tensors are highly compressed representations of the approximated affinity tensor, requiring much smaller memory than in previous methods, which store the full affinity tensor. We compute the principal eigenvector of the approximated affinity tensor using the small bases and index tensors without explicitly storing the approximated tensor. To compensate for the loss of matching accuracy by the approximation, we also adopt and incorporate a marginalization scheme that maps a higher order tensor to matrix as well as a one-to-one mapping constraint into the eigenvector computation process. The experimental results show that the proposed method is faster and requires smaller memory than the existing methods with little or no loss of accuracy.</P>
Global Localization for Mobile Robots using Reference Scan Matching
Park, Soonyong,Park, Sung-Kee 제어로봇시스템학회 2014 Transaction on control, automation and systems eng Vol.12 No.1
This paper presents a new approach based on scan matching for global localization with a metric-topological hybrid world model. The proposed method aims to estimate relative pose to the most likely reference site by matching an input scan with reference scans, in which topological nodes are used as reference sites for pose hypotheses. In order to perform scan matching we apply the spectral scan matching (SSM) method that utilizes pairwise geometric relationships (PGR) formed by fully interconnected scan points. The SSM method allows the robot to achieve scan matching without using an initial alignment between two scans and geometric features such as corners, curves, or lines. The localization process is composed of two stages: coarse localization and fine localization. Coarse localization with 2D geometric histogram constructed from the PGR is fast, but not precise sufficiently. On the other hand, fine localization using the SSM method is comparatively slow, but more accurate. This coarse-to-fine framework reduces the computational cost, and makes the localization process reliable. The feasibility of the proposed methods is demonstrated by results of simulations and experiments.
박순용(SoonYong Park),이설영(Seolyoung Lee) 한국콘텐츠학회 2023 한국콘텐츠학회논문지 Vol.23 No.2
본 연구에서는 신호교차로를 제외한 다양한 교통상황을 고려하기 위하여 비신호교차로, 회전교차로, 연속류 합류부를 대상으로 하여 자율협력주행 차량의 점유율 변화에 따른 교통류 안전성을 검토하였다. 이를 위해 미시적 교통류 프로그램을 활용하여 차량 궤적 기반 교통상황 및 상충분석을 통해 안전성 변화를 분석하였다. 분석방법은 교통류 분석 프로그램인 VISSIM의 차량 운행 파라메타를 자율차에 맞게 조정하여 시뮬레이션을 수행하고, 시뮬레이션에서 도출된 차량 궤적을 기반으로 상충분석을 수행하였다. 비신호 교차로는 자율차 비율 증가에 따라 지체가 감소하여 자율차 증가에 따른 효율적 운영을 확인할 수 있었다. 회전교차로 분석에서는 회전차로 직경 55m(D55)에서는 MPR에 따른 차이가 미비한 반면, 회전차로 직경 25m(D25)와 직경 40m(D40)에서는 MPR(자율차 차량 점유율)이 증가함에 따라 속도가 저하되는 것으로 분석되었으나, 차량당 평균지체는 감소하였다. 연속류 합류부 또한 MPR 증가에 따라 평균 주행속도는 감소하였으나 상충 유형간 뚜렷한 패턴을 나타내지는 않았다. 본 연구를 통해 비신호교차로, 회전교차로, 연속류 합류부에 대하여 자율차 증가 비율에 따른 영향을 검토한 결과, 자율차 비율이 증가할수록 교통류의 안전성은 향상되는 것으로 확인되었다. This study tried to analyze traffic flow safety for autonomous cooperative vehicles’ flows in uncommon situations such as unsignalized intersections, roundabouts, and uninterrupted merging areas according to the MPR(Market Penetration Rate) changes. Micro-traffic simulation program based on traffic trajectory conflict analysis was utilized to derive the traffic safety fluctuation. The analysis was conducted using traffic simulation analysis program VISSIM, using the parameters of autonomous vehicles, and trajectories derived from VISSIM was then used to conduct conflict analysis. For unsignalized intersections, traffic delay reduced as the ratio of autonomous vehicles increased, showing high efficiency with autonomous vehicles. Roundabout conditions showed relatively low difference in accordance with MPR in D55, however in D25 and D40, average traffic speed reduced as MPR increased, while the average delay per vehicles decreased. Uninterrupted merging areas also showed similar patterns as average traffic speed decreased as MPR increased, however it did not show significant conflict patterns. Considering the results of the study, unsignalized intersections, roundabouts and uninterrupted merging areas showed increased traffic flow safety as number of autonomous vehicle increased.