Heesung Chae

Combination of RFID and Vision for Mobile Robot Localization

This paper illustrates an efficient method for global localization incorporating signal detection from artificial landmark consisted of RFID tags, and for fine localization incorporating feature descriptor derived from a view of scene. The system incorporates a RFID reader on a mobile robot checking the signal from RFID tags to localize the robot with respect to global position. After determining the global position of the robot, the feature matching can be used to checking the local position of it in a predetermined global position. And we propose a successive global-to-fine localization algorithm using RFID tags andfeature matching respectively. The experimental results showed the proposed algorithm has improved the localization performance on indoor environments with a mobile robot.

Robot Localization Sensor for Development of Wireless Location Sensing Network

The localization is one of the most important issues for mobile robot. We describe a novel localization sensor suite for the development of a wireless location sensing network. The sensor suite comprises wirelessly controlled infrared landmarks and an image sensor which detects the pixel positions of infrared sources. The proposed sensor suite can operate irrespective of the illumination condition in the indoor environment. We describe the operating principles of the developed sensor suite and report the performance for mobile robot localization and navigation. The advantage of the developed sensor suite lies in its robustness and low cost to obtain localization information as well as simplicity of deployment to build a robot location sensing network. Experimental results show that the developed sensor suite outperforms the state-of-the-art localization sensor

Autonomous navigation of mobile robot based on DGPS/INS sensor fusion by EKF in semi-outdoor structured environment

Although GPS/DGPS become the dominant localization solution in the outdoor environment, it needs assistant sensors or algorithms for the covering the area not to get the position information from GPS. Especially, in the robot navigation, the sensor fusion algorithm is needed. In addition, it is hard to get the position information at the area surrounded the high buildings such as the downtown because GPS signals is so feeble. Therefore, this paper illustrates an efficient method for the outdoor localization incorporating DGPS, Encoder, and IMU sensor based on EKF. To show the localization performances of the proposed fusion algorithm, we have implemented the proposed algorithm and applied the advertising robot platform which is operating well during 80 days in the real semi-outdoor structured environment. The proposed sensor fusion algorithm and the experimental results showed the feasibility of our novel sensor fusion algorithm.

Localization system for mobile robot using wireless communication with IR landmark

The localization of robots is a main problem to solve to make the robots navigate autonomously. This paper introduces an embedded indoor localization system for mobile robot. The system consists of a localization sensor that computes location of itself and infrared landmarks that are wirelessly controlled by the localization sensor. The localization sensor which is combined with an image sensor detects pixel positions of infrared sources from the landmark and by the pixel position the sensor figures out its position(x, y) and heading angle. The coverage of a localization space is enlarged by dynamically combining robot odometer and IR landmark. The advantages of the developed system can be found on its position accuracy, robustness and easy expansion of localization space.

Artificial landmark map building method based on grid SLAM in large scale indoor environment

This paper proposes the artificial landmark map building method using a Grid-based Simultaneous Localization And Mapping (Grid SLAM). The Grid SLAM method is employed to simultaneously localize the position of mapping cart and construct the map of working area. Based on the estimated position of the mapping cart and the grid-based map, the artificial landmarks are localized and their positions are saved to the artificial landmark map. The proposed method reduces the complexity and the cost of mapping process which is usually done by hand. The real implementation has been carried out to build the artificial landmark map of large scale indoor environment named T-City. The implementation results show that the proposed method gives a convenient way to construct the artificial landmark map while still maintaining the accuracy of map. The correctness of the artificial landmark map has been confirmed through the real operation of the mobile robots which rely on the artificial landmark map for their navigation at T-City.

Background-aware pedestrian/vehicle detection system for driving environments

In this paper, we introduce the new approach to enhance the reliability of detection of objects in a driving environment (e.g. pedestrian and vehicle). We present the method of filtering out false positive detections while maintaining true positive detections. Our approach considers that if we remove a certain region from an image taken from a vehicle in a driving environment, the inpainting algorithm is able to restore the removed region based on its surroundings when it does not include objects. Previous inpainting algorithms were used for restoration of damaged paintings, and we expand its usage to confirm whether the detection result includes the real object or not. Furthermore, we introduce a simple but effective speedup method for the sliding window using simple edge features of objects. Experimental results confirm that our approach is able to improve the accuracies of various pedestrian and vehicle detectors. We show the improved accuracy of pedestrian and vehicle detection in a driving environment with various detectors.

Applications of robot navigation based on artificial landmark in large scale public space

This paper presents the navigation technique for service mobile robots in large scale environment using artificial landmark. The robot navigation is comprised of three major components; localization, mapping, and path planning. To implement the stable navigation system of mobile robots, many developers could use the artificial landmark to measure the accurate position of robot in large scale environment. When the mobile robots obtains the position based on the artificial landmark, they need to have the map which contains information about the positions of artificial landmarks. In this paper, Grid-based Simultaneous Localization And Mapping (Grid SLAM) method is employed to construct the map of artificial landmark using a specially made mapping cart. The artificial landmark map has been used for the real operation of four kinds of robots; patrol, guidance, delivery, cafeteria serving, relying on the artificial landmark map for their navigation at the large scale indoor environment named Tomorrow City (T-City) where the artificial landmark system is installed for the robotic technologies. The implementation results show that it is possible for mobile robots to provide various services based on the artificial landmark in large indoor environment.

A Real-time Localization System Based on IR Landmark for Mobile Robot in Indoor Environment

The localization is one of the most important issues for mobile robot. This paper describes a novel localization system for the development of a location sensing network. The system comprises wirelessly controlled infrared landmarks and an image sensor which detects the pixel positions of infrared sources. The proposed localization system can operate irrespective of the illumination condition in the indoor environment. We describe the operating principles of the developed localization system and report the performance for mobile robot localization and navigation. The advantage of the developed system lies in its robustness and low cost to obtain location information as well as simplicity of deployment to build a robot location sensing network. Experimental results show that the developed system outperforms the state-of-the-art localization methods.

Robot task control utilizing human-in-the-loop perception

We propose a network robot application utilizing a human-in-the-loop structure. The proposed structure hybridizes robot perception with perception capability of a human, rendering a robot immune to the uncontrolled environment. Network infrastructure enables the user to intervene in the operation of a robot whenever necessary, enabling seamless transition of task control between the robot and the remote user. We have developed a prototype security robot system by implementing the proposed human-in-the-loop structure. Introduction of network infrastructure, however, also invokes system instability due to network fluctuation, time delay, or jittering. We could resolve the instability by imparting task intelligence to the robot and employing wireless distribution system (WDS) configuration for seamless data communication beyond the coverage of a single access point. Although our approach may solve only part of problems inherent in networked robots, we found that the developed robot system bears sufficient applicability to real world robotic systems incorporating large-area robot navigation.

Automated robotic service in large-scale exhibition environments

This paper describes a concerted effort to realize an automated robotic service in exhibition environments, characterized by a dense population of people with dynamic, random movements and a complex structure with large-scale dimensions. We describe the developed robotic service framework built based on robot navigation function. Spatial representation of the environment is described, on which spatial path planning, robot localization, and remote monitoring and control of individual robots are developed. As observed from a long-term demonstration, the developed robotic system provided intended robotic services for visitors and obtained satisfactory user feedback, which encourages the adoption of automated robotic services in daily environments.