• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.4
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• pp.451-458
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• 2015

This paper handles self-collision avoidance for a rescue robot with redundant manipulators. In order to detect all available self-collisions in advance, minimum distances between arbitrary robot parts should be monitored in real-time. For the minimum distance estimation, we suggest a modified method from a previous skeleton algorithm which has less computation burden and realize collision avoidance based on a potential function using the proposed algorithm. The resultant command by collision avoidance should not disturb a given primary task, so null-space of joint solution from a CLIK is utilized for collision avoidance by a gradient projection method.

• Journal of the Society of Naval Architects of Korea
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• v.38 no.4
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• pp.23-29
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• 2001

An Obstacle Avoidance System(OAS) of Underwater Vehicle(UV) in diving and steering plane is investigated. The concept of Imaginary Reference Line(IRL), which acts as the seabed in the diving plane, is introduced to apply the diving plane avoidance algorithm to the steering plane algorithm. Furthermore, the distance to the obstacle and the slope information of the obstacle are used for more efficient and safer avoidance. As for the control algorithm, the sliding mode controller is adopted to consider the nonlinearity of the equations of motion and to get the robustness of the designed system. To verify the obstacle avoidance ability of the designed system, numerical simulations are carried out on the cases of some presumed three-dimensional obstacles. The effects of the sonar and the clearance factor used in avoidance algorithm are also investigated. Through these, it is found that the designed avoidance system can successfully cope with various obstacles and the detection range of sonar is proven to bea significant parameter to the performance of the avoidance.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.417-422
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• 1993

Robots working in the multiple robot system can perform the variety of tasks compared to the single robot system, while they are subject to the various tight constraints such as the precise coordination and the mutual collision avoidance during the task execution. In this paper, we provide an algorithm and graphical verification for collision avoidance between two robots working together. The algorithm calculates the minimum time delay for collision avoidance and the graphical verification is performed through the 3-D graphic simulator.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.1
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• pp.89-93
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• 2009

This paper deals with obstacle avoidance for unmanned vehicle using stereo system. The "DARPA Grand Challenge 2005" shows that the robot can move autonomously under given waypoint. RADAR, IMS (Inertial Measurement System), GPS, camera are used for autonomous navigation. In this paper, we focus on stereo system for autonomous navigation. Our approach is based on Singh et. al. [5]'s approach that is successfully used in an unmanned vehicle and a planetary robot. We propose an improved algorithm for obstacle avoidance by modifying the cost function of Singh et. al. [5]. Proposed algorithm gives more sharp contrast in choosing local path for obstacle avoidance and it is verified in experimental results.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.4
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• pp.351-359
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• 2010

This paper proposes a linear system control algorithm with collision avoidance in multiple satellites. Consideration of collision avoidance is augmented by adding a weighting term in the cost function of the original tracking problem in linear quadratic control (LQC). Because the proposed algorithm relies on a similar solution procedure to the original LQC, its inherent advantages, including gain-robustness and optimality, are preserved. To confirm and visualize the derived algorithm, a simple example of two-vehicle motion in the two-dimensional plane is illustrated. In addition, the proposed collision avoidance control is applied to satellite formation flying, and verified by numerical simulations.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.3
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• pp.272-281
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• 2013

Traffic Collision Avoidance System (TCAS) is designed to enhance safety in aircraft operations, by reducing the incidences of mid-air collision between aircraft. The current version of TCAS provides only vertical resolution advisory to the pilots, if an aircraft's collision with another is predicted to be imminent, while efforts to include horizontal resolution advisory have been made, as well. This paper introduces a collision resolution algorithm, which includes both vertical and horizontal avoidance maneuvers of aircraft. Also, the paper compares between the performance of the proposed algorithm and that of algorithms with only vertical or horizontal avoidance maneuver of aircraft.

• Journal of Auto-vehicle Safety Association
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• v.5 no.2
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• pp.32-38
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• 2013

This paper presents collision avoidance using model predictive control algorithm. A model predictive control algorithm determines lateral tire force and yaw moment and steering angle input and differential braking input is determined from lateral tire force and yaw moment. A constraint for model predictive control is designed for obstacle avoidance. A objective function is designed to minimize lateral tire force and yaw moment input and to follow changed lane after collision avoidance. The performance of proposed algorithm has been investigated via computer simulation conducted to vehicle dynamic software CARSIM and Matlab/Simulink.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.691-694
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• 2000

In this paper, a motion control algorithm is proposed by using neural network system, which makes a robot arm successfully avoid unexpected obstacle when the robot is moving from the start to the goal position. During the motion, if there is an obstacle the vision system recognizes it. And in every time the optimization-algorithm quickly chooses a motion among the possible motions of robot. The proposed algorithm has a good avoidance characteristic in simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2461-2466
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• 2003

This paper presents a simple sensor fusion algorithm using neural network for navigation of mobile robots with obstacle avoidance and trap recovery. The multiple sensors input sensor data to the input layer of neural network activating the input nodes. The multiple sensors used include optical encoders, ultrasonic sensors, infrared sensors, a magnetic compass sensor, and GPS sensors. The proposed sensor fusion algorithm is combined with the VFH(Vector Field Histogram) algorithm for obstacle avoidance and AGPM(Adaptive Goal Perturbation Method) which sets adaptive virtual goals to escape trap situations. The experiment results show that the proposed low-level fusion algorithm is effective for real-time navigation of mobile robot.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.5
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• pp.291-299
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• 2005

An obstacle avoidance algorithm for a network-based autonomous mobile robot is proposed in this paper. The obstacle avoidance algorithm is based on the VFH(Vector Field Histogram) algorithm and two delay compensation methods with the VFH algorithm are proposed for a network-based robot with distributed environmental sensors, mobile actuators, and the VFH controller. Firstly, the environmental sensor information is compensated by prospection with acquired environmental sensor information, measured network delays, and the kinematic model of the robot. The compensated environmental sensor information is used for building polar histogram with the VFH algorithm. Secondly, a sensor fusion algorithm for localization of the robot is proposed to compensate the delay of odometry sensor information and the delay of environmental sensor information. Through some simulation tests, the performance enhancement of the proposed algorithm in the viewpoint of efficient path generation and accurate goal positioning is shown here.