• International Journal of Aeronautical and Space Sciences
• /
• v.12 no.3
• /
• pp.252-259
• /
• 2011

This paper is focused on dynamic modeling and control system design as well as vision based collision avoidance for multi-rotor unmanned aerial vehicles (UAVs). Multi-rotor UAVs are defined as rotary-winged UAVs with multiple rotors. These multi-rotor UAVs can be utilized in various military situations such as surveillance and reconnaissance. They can also be used for obtaining visual information from steep terrains or disaster sites. In this paper, a quad-rotor model is introduced as well as its control system, which is designed based on a proportional-integral-derivative controller and vision-based collision avoidance control system. Additionally, in order for a UAV to navigate safely in areas such as buildings and offices with a number of obstacles, there must be a collision avoidance algorithm installed in the UAV's hardware, which should include the detection of obstacles, avoidance maneuvering, etc. In this paper, the optical flow method, one of the vision-based collision avoidance techniques, is introduced, and multi-rotor UAV's collision avoidance simulations are described in various virtual environments in order to demonstrate its avoidance performance.

• Proceedings of the KIEE Conference
• /
• 1998.07g
• /
• pp.2360-2362
• /
• 1998

This paper presents a new collison-free trajectory problem for SCARA robot manipulator. we use artificial potential field for collison detection and avoidance. The potential function is typically defined as the sum of attractive potential pulling the robot toward the goal configuration and a repulsive potential pushing the robot away from the obstacles. In here, end-effector of manipulator is represented as a particle in configuration space and moving obstacles is simply represented, too. we consider not fixed obstacle but moving obstacle in random. So, we propose new distance function of artificial potential field with moving obstacle for SCARA robot. At every sampling time, the artificial potential field is update and the force driving manipulator is derived from the gradient vector of artificial potential field. To real-time path planning, we apply very simple modeling to obstacle. Some simulation results show the effectiveness of the proposed approach.

• Journal of Forest and Environmental Science
• /
• v.39 no.4
• /
• pp.254-260
• /
• 2023

A sensor system has been developed that uses an ultrasonic sensor to detect the downhill slope on the side of a forest road and prevents a vehicle-type forest machine from rolling down a mountainside. A specular reflection of ultrasonic wave might cause severe issues in measuring distances to targets. By investigating the installation angle of the sensor to minimize the negative effects of specular reflection, the installation angle of lateral monitoring ultrasonic sensor could be determined based on the width of road shoulder. Obstacles such as small rocks or piece of log in a forest road may cause the forest machine to be overturned while the machine riding over due to excessive its posture change. It was determined that the laser sensor could be a part of a sensor system capable of specifying the location and size of small obstacles. Not only this sensor system including ultrasonic and laser sensors can issue a warning of dangerous sections to drivers in forest forwarders currently in use, but also it can be used as a driving safety sensor in autonomous forest machine or remote-control forest machine in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.11 no.5
• /
• pp.125-135
• /
• 2012

This paper proposes the new object detection system with two laser-scanners and a camera for classifying the objects and predicting the location of objects on road street. This detection system could be applied the new C-ITS service such as ADAS(Advanced Driver Assist System) or (semi-)automatic vehicle guidance services using object's types and precise position. This study describes the some examples in other countries and feasibility of object detection system based on a camera and two laser-scanners. This study has developed the heterogenous sensor's fusion method and shows the results of implementation at road environments. As a results, object detection system at roadside infrastructure is a useful method that aims at reliable classification and positioning of road objects, such as a vehicle, a pedestrian, and obstacles in a street. The algorithm of this paper is performed at ideal condition, so it need to implement at various condition such as light brightness and weather condition. This paper should help better object detection and development of new methods at improved C-ITS environment.

• Journal of The Korean Society For Urban Railway
• /
• v.6 no.4
• /
• pp.269-278
• /
• 2018

Railway obstacle detecion system has been introduced with high-speed railway in 2004 to prevent accidents by obstacles such as landslide, rockfall and things fallen from the gauntry over the railway. But existing system has some limitation for landslide or fallen obstacle over railway. Therefore, In this study, we suggest new advanced obstacle detection system introducing the OTDR, optical fiber fences and detection cameras. This system can detect depression degree by the force to the fences and video for the specific region as well as detection wire Off condition. We produce and functional tests for fiber fence and OTDR, which are the core parts of the development system, and results were obtained to demonstrate improved detection capabilities. Several functions also been tested to verify the advanced detection performance and got some satisfactory results. Further we will conduct environment tests and field test.

• Journal of Institute of Control, Robotics and Systems
• /
• v.9 no.12
• /
• pp.1009-1018
• /
• 2003

In a park or street, we can see many people Jogging or walking with their dogs chasing their masters. In the previous study, an entertainment robot, CARTRI that imitates the dog's behavior was created. The robot's task was chasing a moving goal that was recognized as the master. The physical structure of the CARTRI robot was three-wheel type locomotion system. The sensor system which could detect the position of the master in the outdoor space, was consists of a signal transmitter which was held by the master and five ultrasonic receivers which were mounted on the robot. In the experiment, the robot could chase a human walking in outdoor space like a park. But it could not avoid obstacles and its behavior was only goal-chasing behavior because of the limit of the sensor system. In this study, an improved RF-ultrasonic sensor system which can detect both goal and obstacle is developed in order to enable the CARTRI robot to carry out various behavior. The sensor system has increased angle resolution by using eight ultrasonic receivers instead of five in the previous study. And it can detect obstacle by using reflective type ultrasonic sensors. The sensor system is designed so that detection of goal and obstacle could be conducted in one sampling period. The Performance of the developed sensor system is evaluated through experiments.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
• /
• 2003.11a
• /
• pp.203-207
• /
• 2003

Due to the inherent nature of the low flying UAV, obstacle detection is a fundamental requirement in the flight path to avoid the collision from obstacles as well as manned aircraft. In this paper, a preliminary sensor requirements of an obstacle detection system for UAV in low-altitude flight are analyzed, and the automated obstacle detection sensor system is proposed assessing both passive and active sensors such as EO camera, IR, Laser radar, microwave and millimeter radar. In addition, TCAS (Traffic Alert and Collision Avoidance System) are reviewed for the collision avoidance of the manned aircraft system. It is suggested that small-sized radar sensor is the best candidate for the smart UAV because an active radar can provide the real-time informations on range and range rate in the all-weather environment. However, an important constraints on small UAV should be resolved in terms of accommodation of the mass, volume, and power allocated in the payload of the UAV system design requirements.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.12 no.1
• /
• pp.43-62
• /
• 2017

Mobile pulse scanning Light Detection And Ranging (LIDAR) are essential components of intelligent vehicles capable of autonomous travel. Obstacle detection functions of autonomous vehicles require very low failure rates. With the increasing number of autonomous vehicles equipped with scanning LIDARs to detect and avoid obstacles and navigate safely through the environment, the probability of mutual interference becomes an important issue. The reception of foreign laser pulses can lead to problems such as ghost targets or a reduced signal-to-noise ratio. This paper will show the probability that any two scanning LIDARs will interfere mutually by considering spatial and temporal overlaps. We have conducted four experiments to investigate the occurrence of the mutual interference between scanning LIDARs. These four experimental results introduced the effects of mutual interference and indicated that the interference has spatial and temporal locality. It is hard to ignore consecutive mutual interference on the same line or the same angle because it is possible the real object not noise or error. It may make serious faults because the obstacle detection functions of autonomous vehicle rely on heavily the scanning LIDAR.

• Journal of Korea Game Society
• /
• v.20 no.3
• /
• pp.45-54
• /
• 2020

An automated system using a embedded board is required to generate the notation input of the offline Go game. This paper integrates shape and color information of the objects on the Go game board for light-insensitive processing and reduces the computation step. This paper combined the detection of obstacles using connected components with the computation of canny edge detection and HSV-based detection. As a result, the processing time is reduced in the embedded environment so that reliable notation can be automatically stored even in real-time play environment.

• Journal of the Korea Computer Graphics Society
• /
• v.27 no.5
• /
• pp.63-71
• /
• 2021

Among drone autonomous flight technologies, obstacle avoidance is a very important technology that can prevent damage to drones or surrounding environments and prevent danger. Although the LiDAR sensor-based obstacle avoidance method shows relatively high accuracy and is widely used in recent studies, it has disadvantages of high unit price and limited processing capacity for visual information. Therefore, this paper proposes an obstacle avoidance algorithm for drones using camera-based PPO(Proximal Policy Optimization) reinforcement learning, which is relatively inexpensive and highly scalable using visual information. Drone, obstacles, target points, etc. are randomly located in a learning environment in the three-dimensional space, stereo images are obtained using a Unity camera, and then YOLov4Tiny object detection is performed. Next, the distance between the drone and the detected object is measured through triangulation of the stereo camera. Based on this distance, the presence or absence of obstacles is determined. Penalties are set if they are obstacles and rewards are given if they are target points. The experimennt of this method shows that a camera-based obstacle avoidance algorithm can be a sufficiently similar level of accuracy and average target point arrival time compared to a LiDAR-based obstacle avoidance algorithm, so it is highly likely to be used.