• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.629-634
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• 1995

The purpose of this paper is to develop a method of Collision-Free Path Planning (CFPP) for an articulated robot. First, the configuration of the robot is formed by a set of robot joint angles derived fromm robot inverse kinematics. The joint space that is made of the joint angle set, forms a Configuration space (Cspace). Obstacles in the robot workcell are also transformed and mapped into the Cspace, which makes Cobstacles in the Cspace. (The Cobstacles represented in the Cspace is actually the configurations of the robot causing collision.) Secondly, a connected graph, a kind of roadmap, is constructed from the free configurations in the 3 dimensional Cspace, where the configurations are randomly sampled form the free Cspace. Thirdly, robot paths are optimally in order to minimize of the sum of joint angle movements. A path searching algorithm based on A is employed in determining the paths. Finally, the whole procedures for the CFPP method are illustrated with a 3 axis articulated robot. The main characteristics of the method are; 1) it deals with CFPP for an articulated robot in a 3-dimensional workcell, 2) it guarantees finding a collision free path, if such a path exists, 3) it provides distance optimization in terms of joint angle movements. The whole procedures are implemented by C on an IBM compatible 486 PC. GL (Graphic Library) on an IRIS CAD workstation is utilized to produce fine graphic outputs.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.279-282
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• 1996

Collision avoidance is a method to direct a mobile robot without collision when traversing the environment. This kind of navigation is to reach a destination without getting lost. In this paper, we use a genetic algorithm for the path planning and collision avoidance. Genetic algorithm searches for path in the entire, continuous free space and unifies global path planning and local path planning. It is a efficient and effective method when compared with traditional collision avoidance algorithm.

• 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.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.11
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• pp.36-45
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• 1992

A numerical trajectory planning method for path-constrained trajectory planning is proposed which ensures collision-free and time-optimal motions for two robotic manipulators with limited actuator torques and velocities. For each robot, physical constraints of the robots such as limited torques or limited rotational velocities of the actuators are converted to the constraints on velocity and acceleration along the path, which is described by a scalar variable denoting the traveled distance from starting point. Collision region is determined on the coordination space according to the kinematic structures and the geometry of the paths of the robots. An Extended Coordination Space is then constructed` an element of the space determines the postures and the velocities of the robots, and all the constraints described before are transformed to some constraints on the behaviour of the coordination-velocity curves in the space. A dynamic programming technique is them provided with on the discretized Extended Coordination Space to derive a collision-free and time-optimal trajectory pair. Numerical example is included.

• 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.6 no.3
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• pp.317-328
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• 2000

This paper presents an effective approach to collision-free motion planning of a robot in the work-space including time-varying obstacles. The free arc is defined as a set composed of the configuration points of the robot satisfying collision-free motion constraint at each sampling time. We represent this free arc with respect to the new coordinate frame centered at the goal configuration and there for the collision-free path satisfying motion constraint is obtained by connecting the configuration points of the free arc at each sampling mined from the sequence of free arcs the optimality is determined by the performance index. Therefore the complicated collision-free motion planning problem of a robot is transformed to a simplified SUB_Optimal Collision Avoidance Problem(SOCAP). We analyze the completeness of the proposed approach and show that it is partly guaranteed using the backward motion. Computational complexity of our approach is analyzed theoretically and practical computation time is compared with that of the other method. Simulation results for two cally and practical computation time is compared with that of the other method. Simulation results for two SCARA robot manipulators are presented to verify the efficacy of the proposed method.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2318-2320
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• 1998

A genetic algorithm for global and local path planning and collision avoidance of mobil robot in unstructured workspace 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 KIEE Conference
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• 1999.07g
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• pp.3098-3100
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• 1999

A genetic algorithm for global and local path planning and collision avoidance of mobile robot in dynamic working environment 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 Machine Tool Engineers Conference
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• 2002.04a
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• pp.184-189
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• 2002

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.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.244-249
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• 2001

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.