• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.638-647
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• 1996

Robot manipulators for harvesting fruits must be controlled to track the desired path of end-effector to avoid obstacles under the consideration of collision free area and safety path. This paper presents a robot path control algorithm to secure a collision free area with the recognition of work environments. The flexible space, which does not damage fruits or branches of tree due to their flexibility and physical properties , extends the workspace. Now the task is to control robot path in the extended workspace with the consideration of collision avoidance and velocity limitation at the time of collision concurrently. The feasibility and effectiveness of the new algorithm for redundant manipulators were tested through simulations of a redundant manipulator for different joint velocities.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.233-238
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• 2010

This paper describes a multi-mobile robot system with fuzzy rule based structure in collision avoidance. Collision avoidance is an important function to perform a given task collaboratively and cooperatively in multi-mobile robot environments. So the important but challenging problem is handled in this paper. Considered obstacles for collision avoidance between multi mobile robots are static, dynamic, or both of them at the same time. Using the fuzzy rule based structure, distance and angle from a robot to obstacles are described as fuzzy linguistic values and steering angle for the robot are updated from the collision environments. As a result, the multi-mobile robot can modify a global path from a robot itself to its own target. In addition, avoiding collision with static or dynamic obstacles for the robot system can be achieved. Simulation based experimental results are given to show usefulness of this method.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.176-181
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• 2000

Collision free task planning for dual-arm robot which perform many subtasks in a common work space can be achieved in two steps : path planning and trajectory planning. path planning finds the order of tasks for each robot to minimize path lengths as well as to avoid collision with static obstacles. A trajectory planning strategy is to let each robot move along its path as fast as possible and delay one robot at its initial position or reduce speed at the middle of its path to avoid collision with the other robot.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1140-1143
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• 1996

A new approach based on artificial potential function is proposed for the obstacle avoidance of redundant manipulators. Unlike the so-called "global" path planning method, which requires expensive computation for the path search before the manipulator starts to move, this new approach, "local" path planning, researches the path in real-time using the local distance information. Previous use of artificial potential function has exhibited local minima in some complex environments. This thesis proposes a potential function that has no local minima even for a cluttered environment. This potential function has been implemented for the collision avoidance of a redundant robot in Simulation. The simulation also employ an algorithm that eliminates collisions with obstacles by calculating the repulsive potential exerted on links, based on the shortest distance to object.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.2
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• pp.32-38
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• 1999

An autonomous mobile vehicle for transport system must plan optimal path in work envimnrent without human supervision and obstacle collision. This is to reach a destination without getting lost. In this paper, a genetic algorithm for globaI and local path planning and collision avoidance is proposed. The genetic algorithm searches for a path in the entire and continuous free space and unifies global path planning and local path planning. The sinmulation shows the proposed method is an efficient and effective method when compared with the traditional collision avoidance algorithms.rithms.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.2
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• pp.164-164
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• 1999

An autonomous mobile vehicle for transport system must plan optimal path in work environment without human supervision and obstacle collision. This is to reach a destination without getting lost. In this paper, a genetic algorithm for global and local path planning and collision avoidance is proposed. The genetic algorithm searches for a path in the entire and continuous free space and unifies global path planning and local path planning. The simulation shows the proposed method is an efficient and effective method when compared with the traditional collision avoidance algorithms.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.345-348
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• 1997

In this paper, a motion control algorithm is developed using a fuzzy control and the optimization of performance function, which makes a robot arm avoid an unexpected obstacle when the end-effector of the robot arm is moving to the goal position. During the motion, if there exists no obstacle, the end-effecter of the robot arm moves along the pre-defined path. But if there exists an obstacle and close to the robot arm, the fuzzy motion controller is activated to adjust the path of the end-effector of the robot arm. Then, the robot arm takes the optimal posture for collision avoidance with the obstacle. To show the feasibility of the developed algorithm, numerical simulations are carried out with changing both the positions and sizes of obstacles. It was concluded that the proposed algorithm gives a good performance for obstacle avoidance.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.8
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• pp.165-173
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• 1998

In this paper, a motion control algorithm is developed by using fuzzy control technique, which makes a robot arm avoid unexpected obstacles when the robot is moving from the start to a goal posture. During the motion, if there exist no obstacles the robot arm moves along the pre-defined path. But if some obstacles are recognized and close to the robot arm, a fuzzy controller is activated to adjust the path of the robot arm. To show the feasibility of the developed algorithm, numerical simulations and experiments are carried out. In the experiments, redundant planar robot arms are considered for the collision avoidance test, and it was proved that the developed algorithm gives good collision avoiding performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.592-598
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• 2008

This paper presents collision prediction and avoidance method for AGVS (Automatic Guide Vehicle System). Also, we propose the PO(Right of Path Occupying) with decentralized delay time for collision avoidance. Classified essential element of AGV's working environment is modeled in this paper. Using this model, we propose a new shortest path algorithm using A* search algorithm and obtain the information on AGVs travel time, coordinates and rotation vector. Finally, we use the AGVs information data as input for simulation program. The simulation practice is used in order to evaluate a collision prediction and avoidance, and it has been presented to demonstrate the applicability of the minimize delay time.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.1
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• pp.187-194
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• 2012

This paper compares two collision avoidance algorithms using a simulator. The collision avoidance is vital for autonomous navigation of a mobile robot. Artificial potential field method and elastic force method are major approaches for the collision avoidance. The two algorithms are compared in the respect of the time for motion completion and the length of the motion path. The simulator is developed based on IPC(Inter Process Communication) and a differential drive mobile robot is used for the comparison.