• 한국멀티미디어학회논문지
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• 제25권2호
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• pp.297-310
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• 2022

Road facilities such as CCTV poles have potential risk of collision accidents with a car. A collision detection algorithm installed in the facility allows the collision accident to be known remotely. Most collision detection algorithms are operated by simply focusing on whether a collision have occurred, because these methods are used to measure only acceleration data from a 3-axis sensor to detect collision. However, it is difficult to detect other detailed information such as malfunction of the sensor, collision direction and collision strength, because it is not known without witness the accident. Therefore, we proposed enhanced detection algorithm to get the collision direction, and the collision strength from the tilt of the facility after accident using a 9-axis sensor in this paper. In order to confirm the performance of the algorithm, an accuracy evaluation experiment was conducted according to the data measurement cycle and the invocation cycle to an detection algorithm. As a result, the proposed enhanced algorithm confirmed 100% accuracy for 50 weak collisions and 50 strong collisions at the 9-axis data measurement cycle of 10ms and the invocation cycle of 1,000ms. In conclusion, the algorithm proposed is expected to provide more reliable and detailed information than existing algorithm.

• 대한전자공학회논문지
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• 제26권11호
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• pp.1770-1781
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• 1989

Two robots working in a common workspace may collide with each other. In this paper, a collision-free motion planning algorithm using view time concept is proposed to detect and avoid collision before robot motion. Collision may occur not only at the robot end effector but also at robot links. To detect and avoid potential collisions, the trajectory of the first robot is sampled periodically at every view time and the region in Cartesian space swept by the first robot is viewed as an obstacle during a single sampling period. The forbidden region in the joint constraint map (JCM). The JCM's are obtained in this way at every view time. An algorithm is established for collision-free motion planning of the two robot system from the sequence of JCM's and it is verified by simulations.

• 한국항공운항학회지
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• 제29권4호
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• pp.37-44
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• 2021

In case of South Korea, the airspace which airlines can operate is extremely limited due to the military operational area located within the Incheon flight information region. As a result, safety problems such as mid-air collision between aircraft or Traffic alert and Collision Avoidance System Resolution Advisory (TCAS RA) may occur with higher probability than in wider airspace. In order to prevent such safety problems, an mid-air collision risk detection model based on Detect-And-Avoid (DAA) well clear metrics is investigated. The model calculates the risk of mid-air collision between aircraft using aircraft trajectory data. In this paper, the practical use of DAA well clear metrics based model has been validated. Aviation safety data such as aviation safety mandatory report and Automatic Dependent Surveillance Broadcast is used to measure the performance of the model. The attributes of individual aircraft track data is analyzed to correct the threshold of each parameter of the model.

• 로봇학회논문지
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• 제12권3호
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• pp.258-262
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• 2017

In this paper, we propose a new collision detection algorithm for human-robot collaboration. We use an IMU sensor located at the tip of the manipulator and the kinematic behavior of the manipulator to detect the unexpected collision between the robotic manipulator and environment. Unlike other method, the developed algorithm uses only the kinematic relationship between the manipulator joint and the end effector. Therefore, the collision estimation signal is not affected by the error of the dynamics model. The proposed collision detection algorithm detects the collision by comparing the estimated acceleration of the end effector derived from the position, velocity and acceleration trajectories of the robot joints with the actual acceleration measured by the sensor. In simulation, we compare the performance of our method with the conventional Residual Observer (ROB). Our method is less sensitive to the load variation because of the independency on the dynamic modeling of the manipulator.

• 로봇학회논문지
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• 제15권2호
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• pp.169-176
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• 2020

This paper studied the collision detection of robot manipulators for safe collaboration in human-robot interaction. Based on sensor-based collision detection, external torque is detached from subtracting robot dynamics. To detect collision using joint torque sensor data, a comparative study was conducted using data-based machine learning algorithm. Data was collected from the actual 3 degree-of-freedom (DOF) robot manipulator, and the data was labeled by threshold and handwork. Using support vector machine (SVM), decision tree and k-nearest neighbors KNN method, we derive the optimal parameters of each algorithm and compare the collision classification performance. The simulation results are analyzed for each method, and we confirmed that by an optimal collision status detection model with high prediction accuracy.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2006년도 추계공동학술대회
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• pp.239-254
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• 2006

In mold structure machining, tool interference is a phenomenon which results from a collision between a blade of tool and a workpiece. Also tool collision is a phenomenon which results from a collision of holder with the object to be machined. These phenomena not only cause damages to mold and tool but also increase machining time and cost. To detect a collision of a tool to mold structure, first of all, the mold structure and a tool must be defined with famous geometric models such CSG, B-rep, and Voxel. A tool is defined as a combination of the blade, the shank, and the holder. This thesis reviews various collision detection algorithms using z-map and computer 3D graphic collision detection algorithms for the tool in machining a mold structure.

• 대한전자공학회논문지TC
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• 제45권5호
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• pp.12-20
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• 2008

RFID(Radio frequency identification) 기술은 어떤 사물에 부착되는 태그(Tag)의 고유정보를 리더(Reader)를 사용하여 비접촉 방식으로 식별하는 기술로, 현재 유비쿼터스 센서 네트워크(Ubiquitous Sensor Network) 구현의 핵심기술로 고려되고 있다. 특히 유통 물류분야에 적용되는 UHF대역 RFID시스템은 리더가 인식해야 할 태그의 수가 상당히 많아 태그충돌(Tag-collision)이라는 부정적인 영향이 발생하고, UHF대역 RFID기술 표준인 EPCglobal Gen2 protocol에서는 이런 태그충돌을 해결하기 위해 Slotted Random Anti-collision algorithm을 제시하고 있다. 본 논문에서는 이런 태그충돌의 영향을 최소화하고 전체 시스템의 효율을 보다 향상시키기 위하여 주어진 환경에 유동적으로 리더의 신호 전송전력을 조절하는 전력상승기법(Power Increasing Method)을 제안하고 그것을 주어진 환경에 동적으로 적용함으로써 Gen2에서 제시한 알고리즘보다 개선된 성능을 검증하였다.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2015년도 하계학술대회
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• pp.13-16
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• 2015

In any mobile ad hoc environment, collision amongst mobile objects is always likely to occur unless there is a certain level of intelligence to detect and avoid the collision. This phenomenon of detection and avoidance is the key attribute for safety applications in vehicle to pedestrian (V2P) communications systems. In this paper, we propose a V2P communications concept for collision detection and avoidance.

• ETRI Journal
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• 제45권2호
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• pp.329-337
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• 2023

For safe last-mile autonomous robot delivery services in complex environments, rapid and accurate collision prediction and detection is vital. This study proposes a suitable neural network model that relies on multiple navigation sensors. A light detection and ranging technique is used to measure the relative distances to potential collision obstacles along the robot's path of motion, and an accelerometer is used to detect impacts. The proposed method tightly couples relative distance and acceleration time-series data in a complementary fashion to minimize errors. A long short-term memory, fully connected layer, and SoftMax function are integrated to train and classify the rapidly changing collision countermeasure state during robot motion. Simulation results show that the proposed method effectively performs collision prediction and detection for various obstacles.

• 제어로봇시스템학회논문지
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• 제21권12호
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• pp.1089-1099
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• 2015

This paper proposes vision-based collision risk estimation method for an unmanned surface vehicle. A robust image-processing algorithm is suggested to detect target obstacles from the vision sensor. Vision-based Target Motion Analysis (TMA) was performed to transform visual information to target motion information. In vision-based TMA, a camera model and optical flow are adopted. Collision risk was calculated by using a fuzzy estimator that uses target motion information and vision information as input variables. To validate the suggested collision risk estimation method, an unmanned surface vehicle experiment was performed.