• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1004-1008
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• 1990

This research focuses on developing a new and computationally efficient algorithm for free space structuring and planning collision free paths for an autonomous mobile robot working in an environment populated with polygonal obstacles. The algorithm constructs the available free space between obstacles in terms of free convex area. A collision free path can be efficiently generated based on a graph constructed using the midpoints of common free links between free convex area as passing points. These points correspond to nodes in a graph and the connection between them within each convex area as arcs in this graph. The complexity of the search for collision free path is greatly reduced by minimizing the size of the graph to be searched concerning the number of nodes and the number of arcs connecting them. The analysis of the proposed algorithm shows its efficiency in terms of computation ability, safety and optimality.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.743-747
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• 1996

A Potential Field Method is applied to the proposed algorithm for the planning of collision-free paths of redundant manipulators. The planning is carried out on the base of kinematic configuration. To make repulsive potentials, sources are distributed on the boundaries of obstacles. To escape from local minimum of the main potential and to attack other difficulties of the planning, various potentials are defined simultaneously, Inverse Kinematics Problems of the redundant manipulators are solved by unconstrained optimization method. Computer simulation result of the path planning is presented.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.4
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• pp.579-588
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• 1996

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 built by a set of robot joint angles derived from robot inverse kinematics. The joint space, that is made of the joint angle set, forms a Configuration space (Cspcce). Obstacles in the robot workcell are also transformed into the Cobstacles using slice projection method. Actually the Cobstacles means the configurations of the robot causing collision with obstacles. Secondly, a connected graph, a kind of roadmap, is constructed by the free configurations in the Cspace, where the free configurations are randomly sampled from a free Cspace immune from the collision. Thirdly, robot paths are optimally determinant in the connected graph. A path searching algorithm based on $A^*$ is employed in determining the paths. Finally, the whole procedures for the CFPP method are shown for a proper articulated robot as an illustrative example.

• 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.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.113-118
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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.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1496-1499
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• 2004

In this paper, we deal with a novel path planning algorithm to find collision-free path for a moving robot to find an appropriate path from initial position to goal position. The robot should make progress by avoiding obstacles located at unknown position. Such problem is called the path planning. We propose so called the subgoal generation algorithm to find an effective collision-free path. The generation and selection of the subgoal are the key point of this algorithm. Several subgoals, if necessary, are generated by analyzing the map information. The subgoal is the candidate for the final path to be pass through. Then selection algorithm is executed to choose appropriate subgoal to construct a correct path. Deep and through explanations are given for the proposed algorithm. Simulation example is given to show the effectiveness of the proposed algorithm.