• Journal of Institute of Control, Robotics and Systems
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• v.9 no.1
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• pp.73-81
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• 2003

An autonomous stair robot recognizing the stair, and climbing up and down the stair by utilizing a robot vision, photo sensors, and appropriate climbing algorithm is introduced. Four arms associated with four wheels make the robot climb up and down more safely and faster than a simple track typed robot. The robot can adjust wheel base according to the stair width, hence it can adopt to a variable width stair with different algorithms in climbing up and down. The command and image data acquired from the robot are transferred to the main computer through RF wireless modules, and the data are delivered to a remote computer via a network communication through a proper data compression, thus, the real time image monitoring is implemented effectively.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1201-1211
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• 2015

WSN acts as an effective tool for tracking the large scale environments. In such environment, the battery life of the sensor networks is limited due to collection of the data, usage of sensing, computation and communication. To resolve this, a mobile robot is presented to identify the data present in the partitioned sensor networks and passed onto the sink. In novel data collection algorithm, the performance of the data collecting operation is reduced because mobile robot can be used only within the limited range. To enhance the data collection in a changing environment, Non Linear Error Identifier (NLEI) algorithm has been developed and presented in this paper to configure the robot by means of error models which are non-linear. Experimental evaluation has been conducted to estimate the performance of the proposed NLEI and it has been observed that the proposed NLEI algorithm increases the error correction rate upto 42% and efficiency upto 60%.

• The Journal of Korea Robotics Society
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• v.4 no.3
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• pp.169-176
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• 2009

Low-cost sensors have been widely used for mobile robot navigation in recent years. However, navigation performance based on low-cost sensors is not good enough to be practically used. Among many navigation techniques, building of an accurate map is a fundamental task for service robots, and mapping with low-cost IR sensors was investigated in this research. The robot's orientation uncertainty was considered for mapping by modifying the Bayesian update formula. Then, the data association scheme was investigated to improve the quality of a built map when the robot's pose uncertainty was large. Six low-cost IR sensors mounted on the robot could not give rich data enough to align the range data by the scan matching method, so a new sample-based method was proposed for data association. The real experiments indicated that the mapping method proposed in this research was able to generate a useful map for navigation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.6
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• pp.3023-3031
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• 2013

In this paper, we propose a robot control data generation system applying context aware mechanism in order to control the robot manipulator which automatically sorts parcels. The context aware mechanism generates intelligent information to control a robot using context data such as the parcel shape, weight, location and barcodes. The proposed system collects context data of the parcel and generates robot control data to pick up and drop parcels. Then a robot manipulator, which receives control data of picking-up and dropping, processes the automated sorting of parcels according to delivery persons and delivery routes. It will contribute not only to save much time and cost but also to reduce the industrial accidents.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.9
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• pp.821-829
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• 2014

This paper describes the development of a wireless communication controller of gripper contact signal for industrial robot. The wireless communication gripper controller is composed of a robot wireless communication controller and a gripper wireless transmitting/receiving controller. The robot wireless communication controller transmits the data of gripper sensors, and the gripper wireless communication controller receives the data. And the controller sends the data to the robot controller of industrial robot. As a result of the characteristics test of the wireless communication gripper controller, it is thought that the robot wireless communication controller A transmits and receives three gripper wireless transmitting/receiving controller A1, A2, A3 another. Thus, the developed wireless communication gripper controller can be used for transmitting/ receiving the data of gripper sensors for industrial robot.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1249-1252
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• 1996

With the expansion of research and development for the CIM and the IMS, the importance of introducing the communication network is being increased. This paper presents an implementation of robot workcell by using Fieldbus and investigates data operation of the robot workcell. Through experiments, the operations of periodic and real-time data, and non-periodic real-time data are studied. Also, the relationship between the network transmission rate and the monitoring results from the sensor is analyzed.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.2
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• pp.381-389
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• 2012

This paper proposes a method which corrects location data of GPS for navigation of outdoor mobile robot. The method uses a Bayesian filter approach called the particle filter(PF). The method iterates two procedures: prediction and correction. The prediction procedure calculates robot location based on translational and rotational velocity data given by the robot command. It incorporates uncertainty into the predicted robot location by adding uncertainty to translational and rotational velocity command. Using the sensor characteristics of the GPS, the belief that a particle assumes true location of the robot is calculated. The resampling from the particles based on the belief constitutes the correction procedure. Since usual GPS data includes abrupt and random noise, the robot motion command based on the GPS data suffers from sudden and unexpected change, resulting in jerky robot motion. The PF reduces corruption on the GPS data and prevents unexpected location error. The proposed method is used for navigation of a mobile robot in the 2011 Robot Outdoor Navigation Competition, which was held at Gwangju on the 16-th August 2011. The method restricted the robot location error below 0.5m along the navigation of 300m length.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.3_1spc
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• pp.558-565
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• 2013

This paper describes a whole-body (human body's) motion generation scheme for an android robot that uses motion capture device and a nonlinear constrained optimization method. Because the captured motion data are based on global coordinates and the actors have different heights and different upper-lower body ratios, the captured motion data cannot be used directly for a humanoid robot. In this paper, we suggest a method for obtaining robot joint angles, which allow the resultant robot motion to be as close as possible to the captured human motion data, by applying a nonlinear constrained optimization method. In addition, the results are animated to demonstrate the similarity of the motions.

• Journal of Sensor Science and Technology
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• v.33 no.1
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• pp.18-23
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• 2024

Humanoid robots, designed to interact in human environments, require stable mobility to ensure safety. When a humanoid robot falls, it causes damage, breakdown, and potential harm to the robot. Therefore, fall detection is critical to preventing the robot from falling. Prevention of falling of a humanoid robot requires an operator controlling a crane. For efficient and safe walking control experiments, a system that can replace a crane operator is needed. To replace such a crane operator, it is essential to detect the falling conditions of humanoid robots. In this study, we propose falling detection methods using Convolution Neural Network (CNN) model. The image data of a humanoid robot are collected from various angles and environments. A large amount of data is collected by dividing video data into frames per second, and data augmentation techniques are used. The effectiveness of the proposed CNN model is verified by the experiments with the humanoid robot MAX-E1.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.43-48
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• 2005

A robot system encompassing a remote control and monitoring through a virtual robot design is addressed and a tracking problem for a 2D (2 dimension) moving target by a robot vision is chosen as a case study. The virtual robot is developed, and it synchronizes with the real robot by compensating delay time. Two systems are displayed on a remote panel by communicating command and image data. The virtual robot utilizes an OpenGL library in Visual $C^{++}$ environment. Additionally, the remote monitoring and control between the real robot and the virtual robot are accomplished by employing an appropriate data compression in a network communication.