• The Journal of Korea Robotics Society
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• v.17 no.4
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• pp.397-406
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• 2022

This paper presents an autonomous mobile robot (AMR) system and operation algorithms for logistic and factory facilities without magnet-lines installation. Unlike widely used AMR systems, we propose an EKF-based loosely coupled fusion of LiDAR measurements and visual markers. Our method first constructs occupancy grid and visual marker map in the mapping process and utilizes prebuilt maps for precise localization. Also, we developed a waypoint-based navigation pipeline for robust autonomous operation in unconstrained environments. The proposed system estimates the robot pose using by updating the state with the fusion of visual marker and LiDAR measurements. Finally, we tested the proposed method in indoor environments and existing factory facilities for evaluation. In experimental results, this paper represents the performance of our system compared to the well-known LiDAR-based localization and navigation system.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.2
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• pp.102-108
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• 2008

This paper describes a mapping and localization based on wave algorithm[11] and Kalman filter for effective SLAM. Each robot in a multi robot system has its own task such as building a map for its local position. By combining their data into a shared map, the robot scans actively seek to verify their relative locations. For simultaneous localization the algorithm which is well known as Kalman Filter (KF) is used. For modelling the robot position we wish to know three parameters (x, y coordinates and its orientation) which can be combined into a vector called a state variable vector. The Kalman Filter is a smart way to integrate measurement data into an estimate by recognizing that measurements are noisy and that sometimes they should ignored or have only a small effect on the state estimate. In addition to an estimate of the state variable vector, the algorithm provides an estimate of the state variable vector uncertainty i.e. how confident the estimate is, given the value for the amount of error in it.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.12
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• pp.1232-1239
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• 2009

This paper proposes an exploration strategy to efficiently find a specific place in large unknown environments with wall-following based path planning. Many exploration methods proposed so far showed good performance but they focused only on efficient planning for modeling unknown environments. Therefore, to successfully accomplish the room finding task, two additional requirements should be considered. First, suitable path-planning is needed to recognize the room number. Most conventional exploration schemes used the gradient method to extract the optimal path. In these schemes, the paths are extracted in the middle of the free space which is usually far from the wall. If the robot follows such a path, it is not likely to recognize the room number written on the wall because room numbers are usually too small to be recognized by camera image from a distance. Second, the behavior which re-explores the explored area is needed. Even though the robot completes exploration, it is possible that some rooms are not registered in the constructed map for some reasons such as poor recognition performance, occlusion by a human and so on. With this scheme, the robot does not have to visit and model the whole environment. This proposed method is very simple but it guarantees that the robot can find a specific room in most cases. The proposed exploration strategy was verified by various experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.3
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• pp.265-275
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• 2015

This paper describes extraction methods of five different types of geometrical features (line, arc, corner, polynomial curve, NURBS curve) from the obtained raw data by using a two-dimensional laser range finder (LRF). Natural features with their covariance matrices play a key role in the realization of feature-based simultaneous localization and mapping (SLAM), which can be used to represent the environment and correct the pose of mobile robot. The covariance matrices of these geometrical features are derived in detail based on the raw sensor data and the uncertainty of LRF. Several comparison are made and discussed to highlight the advantages and drawbacks of each type of geometrical feature. Finally, the extracted features from raw sensor data obtained by using a LRF in an indoor environment are used to validate the proposed extraction methods.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.261-262
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• 2023

거동이 불편한 사람의 경우 직접적인 제어보다 손동작으로 간접적인 제어를 함으로써 생활에 어려움이 줄고 편리한 사용이 가능하다. 사람을 인식 후 판단하고 제어가 가능할 뿐만 아니라 손동작 인식이 가능한 선풍기가 사람들에게 더 편하게 활용되고, 간단한 동작으로 제어할 수 있다. 본 논문에서는 Mediapipe를 활용하여 간단한 손동작을 바탕으로 실시간으로 풍속을 제어하고 사람을 인식하는 기능을 제공한다. 야외나 에어컨이 없는 장소의 경우 SLAM을 활용해 주행이 가능한 이동식 선풍기를 개발했다. 기존의 선풍기의 직접적인 조작 제어가 불편한 것이 누구나 쉽게 간단한 손동작을 통해 먼 거리에서의 인식을 통한 제어와 이동 기능이 기존 기능에 비해 향상됨을 기대할 수 있다.

• Journal of Advanced Navigation Technology
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• v.18 no.2
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• pp.134-141
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• 2014

Mobile robots use various sensors for navigation such as wheel encoder, vision sensor, sonar, and laser sensors. Dead reckoning is used with wheel encoder, resulting in the accumulation of positioning errors. For that reason wheel encoder can not be used alone. Too much information of vision sensors leads to an increase in the number of features and complexity of perception scheme. Also Sonar sensor is not suitable for positioning because of its poor accuracy. On the other hand, laser sensor provides accurate distance information relatively. In this paper we propose to extract the angular information from the distance information of laser range finder and use the Kalman filter that match the heading and distance of the laser range finder and those of wheel encoder. For laser scanner with one feature point error may increase much when the feature point is variant or jumping to a new feature point. To solve the problem, we propose to use two feature points and show that the positioning error can be reduced much.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1545-1550
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• 2022

In this research, a method for minimizing the replacement time of AMR (Autonomous Mobile Robot), which is used in various industrial groups such as logistics and manufacturing, was studied in the event of a LiDAR failure. In this regard, a general LiDAR exchange process was defined and a new exchange process based on the newly designed jig, which is mounted on the AMR, for the quick change of LiDAR was proposed. The experiment is conducted using commercialized AMR which was developed for application in the factory of an automobile manufacturing company. It was confirmed that LiDAR can be replaced and aligned within 24 minutes when the new exchange process is employed, which is about 76% or more shorter than the general LiDAR exchange process. As a result, we can minimize AMR downtime and overall process delays by applying the proposed process.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.85-90
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• 2022

In this study, to reduce the time and cost disadvantages of the traditional motion graphic production method in order to realize the movement of a virtual camera identical to that of the real camera, motion graphics virtualization using AR Core-based mobile device real-time tracking data A method for creating a camera is proposed. The proposed method is a method that simplifies the tracking operation in the video file stored after shooting, and simultaneously proceeds with shooting on an AR Core-based mobile device to determine whether or not tracking is successful in the shooting stage. As a result of the experiment, there was no difference in the motion graphic result image compared to the conventional method, but the time of 6 minutes and 10 seconds was consumed based on the 300frame image, whereas the proposed method has very high time efficiency because this step can be omitted. At a time when interest in image production using virtual augmented reality and various studies are underway, this study will be utilized in virtual camera creation and match moving.

• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.66-75
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• 2010

In Augmented Reality, it needs restoration and tracking of a real-time scene structure for the augmented 3D model from input video or images. Most of the previous approaches construct accurate 3D models in advance and try to fit them in real-time. However, it is difficult to measure 3D model accurately and requires long pre-processing time to construct exact 3D model specifically. In this research, we suggest a real-time scene structure analysis method for the wide indoor mobile augmented reality, using only generic models without exact pre-constructed models. Our approach reduces cost and time by removing exact modeling process and demonstrates the method for restoration and tracking of the indoor repetitive scene structure such as corridors and stairways in different scales and details.