• Journal of the Korean Society for Precision Engineering
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• v.17 no.8
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• pp.189-197
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• 2000

This paper addresses that the autonomous mobile robot with the function of teaching a moving path by speech and avoiding a collision is developed. The use of human speech as the teaching method provides more convenient user-interface for a mobile robot. In speech recognition system a speech recognition algorithm using neural is proposed to recognize Korean syllable. For the safe navigation the autonomous mobile robot needs abilities to recognize a surrounding environment and to avoid collision with obstacles. To obtain the distance from the mobile robot to the various obstacles in surrounding environment ultrasonic sensors is used. By the navigation algorithm the robot forecasts the collision possibility with obstacles and modifies a moving path if it detects a dangerous obstacle.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.475-475
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• 2000

This paper describes the construction of an autonomous mobile robot with functions of collision avoidance and speech recognition that is used for teaching path of the robot. The human voice as a teaching method provides more convenient user-interface to mobile robot. For safe navigation, the autonomous mobile robot needs abilities to recognize surrounding environment and avoid collision. We use u1trasonic sensors to obtain the distance from the mobile robot to the various obstacles. By navigation algorithm, the robot forecasts the possibility of collision with obstacles and modifies a path if it detects dangerous obstacles. For these functions, the robot system is composed of four separated control modules, which are a speech recognition module, a servo motor control module, an ultrasonic sensor module, and a main control module. These modules are integrated by CAN(controller area network) in order to provide real-time communication.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.10
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• pp.928-933
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• 2012

In this paper, the IR and compass sensors for the underwater system were used. The walls of the water tank have been recognized and avoided treating the walls as obstacles by the bio-mimetic underwater robot. This paper is consists of two parts: 1.The hardware part for the IR and compass sensors and 2.The software part for obstacle avoidance algorithm while the bio-mimetic robot is swimming with the obstacle recognition. Firstly, the hardware part controls through the RS-485 communications between a microcontroller and the bio-mimetic underwater robot. The software part is simulated for obstacle recognition and collision avoidance based upon the data from IR and compass sensors. Actually, the bio-mimetic underwater robot recognizes where is the obstacle as well as where is the bio-mimetic robot itself while it is moving in the water. While the underwater robot is moving at a constant speed recognizing the wall of water tank as an obstacle, an obstacle avoidance algorithm is applied for the wall following swimming based upon the IR and compass sensor data. As the results of this research, it is concluded that the bio-mimetic underwater robot can follow the wall of the water tank efficiently, while it is avoiding collision to the wall.

• The Journal of Korea Robotics Society
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• v.11 no.2
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• pp.108-114
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• 2016

This paper presents a sensor-based cane mechanism for walking aid of the visually impaired person. We also describe an approach to decide properly the length of the specified cane mechanism. The cane mechanism has some sensors to identify the possibility of a collision between the cane user and an object and/or a person, and a signal processing unit that enables the user to recognize such a collision is attached in the mechanism. Thus, the walker using this cane can recognize in advance the possibility of such a collision in his walking process. Consequently, it is helpful for the visually impaired person to walk on a pedestrian road safely. The feature of the proposed cane mechanism and its availability have been shown through experimental works in a typical walking environment.

• Transactions of the Korean Society of Automotive Engineers
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• v.25 no.3
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• pp.309-316
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• 2017

In shuttle vans designed to transport children, the recognition of a child's approach and departure is very important. Ultrasonic sensors are generally used for a short distance around a vehicle. Although ultrasonic sensors are cheaper than other ADAS sensors, the number of sensors installed in a van should be optimized. In order to recognize the presence of a child around a shuttle van, this paper proposes the placement of ultrasonic sensors in the van. Considering the turning radius of the van and the distance from each sensor to a child, collision risk is classified as 'safe', 'warning', and 'danger'. The sensor placement and the recognition algorithm are verified in a virtual driving environment.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.219-225
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• 2008

This study developed a surveillance robot for a ship. The developed robot consists of ultrasonic sensors, an actuator, a lighting fixture and a camera. The ultrasonic sensors are used to avoid collision with obstacles in the environment. The actuator is a servo motor system. The developed robot has four drive wheels for driving. The lighting fixture is used to guide the robot in a dark environment. To transmit an image, a camera with a pan moving and a tilt moving is equipped on the upper part of the robot. AdaBoost algorithm trained with 15 features, is used for face recognition. In order to evaluate the face recognition of the developed robot, experiments were performed.

• Journal of Aerospace System Engineering
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• v.17 no.6
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• pp.16-26
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• 2023

With the growing demand for unmanned aerial vehicles (UAVs), various collision avoidance methods have been proposed, mainly using LiDAR and stereo cameras. However, it is difficult to apply these sensors to small UAVs due to heavy weight or lack of space. The recently proposed methods use a combination of object recognition models and distance sensors, but they lack information on the obstacle size. This disadvantage makes distance determination and obstacle coordination complicated in an early-stage collision avoidance. We propose a method for estimating obstacle sizes using a monocular camera-YOLO and infrared sensor. Our experimental results confirmed that the accuracy was 86.39% within the distance of 40 cm. In addition, the proposed method was applied to a small UAV to confirm whether it was possible to avoid obstacle collisions.

• Journal of Aerospace System Engineering
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• v.15 no.1
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• pp.102-110
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• 2021

Recently, multi-copters equipped with various collision avoidance sensors have been introduced to improve flight stability. LiDAR is used to recognize a three-dimensional position. Multiple cameras and real-time SLAM technology are also used to calculate the relative position to obstacles. A three-dimensional depth sensor with a small process and camera is also used. In this study, a small collision-avoidance multi-copter system capable of in-door flight was developed as a platform for the development of collision avoidance software technology. The multi-copter system was equipped with LiDAR, 3D depth sensor, and small image processing board. Object recognition and collision avoidance functions based on the YOLO algorithm were verified through flight tests. This paper deals with recent trends in drone collision avoidance technology, system design/manufacturing process, and flight test results.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.5
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• pp.547-553
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• 2021

Dynamic object recognition is an important task for autonomous vehicles. Since dynamic objects exhibit a higher collision risk than static objects, our own trajectories should be planned to match the future state of moving elements in the scene. Time information such as optical flow can be used to recognize movement. Existing optical flow calculations are based only on camera sensors and are prone to misunderstanding in low light conditions. In this regard, to improve recognition performance in low-light environments, we applied a normalization filter and a correction function for Gamma Value to the input images. The low light quality improvement algorithm can be applied to confirm the more accurate detection of Object's Bounding Box for the vehicle. It was confirmed that there is an important in object recognition through image prepocessing and deep learning using YOLO.

• The Journal of Korea Robotics Society
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• v.15 no.1
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• pp.55-61
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• 2020

Getting on and off an elevator is one of the most important parts for multi-floor navigation of a mobile robot. In this study, we proposed the method for the pose recognition of elevator doors, safe path planning, and motion estimation of a robot using RGB-D sensors in order to safely get on and off the elevator. The accurate pose of the elevator doors is recognized using a particle filter algorithm. After the elevator door is open, the robot builds an occupancy grid map including the internal environments of the elevator to generate a safe path. The safe path prevents collision with obstacles in the elevator. While the robot gets on and off the elevator, the robot uses the optical flow algorithm of the floor image to detect the state that the robot cannot move due to an elevator door sill. The experimental results in various experiments show that the proposed method enables the robot to get on and off the elevator safely.