• 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.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.2
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• pp.65-71
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• 2018

In order to make the underwater vehicle carry out the mission in a submarine environment, it is needed to plan a safe and efficient route to a given destination and prevent the autonomous submersible from colliding with obstacles while moving along the planned route. The function of collision avoidance makes the travel distance of the autonomous submersible longer. Moreover, it should move slowly near to obstacles against their moving disturbance. As a result, this invokes the degradation of the navigation efficiency in the process of collision avoidance. The side effect of the collision avoidance is not ignorable in the case of high congested environments such as the coast with many obstacles. In this paper, we suggest a path planning method which provides the route with minimum travel time considering collision avoidance in congested environment. For the purpose, we define environmental congestion map related to geometric information and obstacles. And we propose a method to consider the moving cost in the RRT scheme that provides the existing minimum distance path. We verified that the efficiency of our algorithm with simulation experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.211-217
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• 2014

This paper addresses an algorithm of path planning for autonomous driving of a ground vehicle in waypoint navigation. The proposed algorithm is flexible in utilization under a large GPS positioning error and generates collision-free multiple paths while pursuing minimum traveling time. An optimal path reduces inefficient steering by minimizing lateral changes in generated waypoints along a path. Simulation results compare the proposed algorithm with the A* algorithm by manipulation of the steering wheel and traveling time, and show that the proposed algorithm realizes real-time obstacle avoidance by quick processing of path generation, and minimum time traveling by producing paths with small lateral changes while overcoming the very irregular positioning error from the GPS.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.4
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• pp.403-413
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• 1990

A collision free trajectory control for multiple mobile robots in obstacle-resident workspace is proposed. The proposed method is based on the concept of neural optimization network which has been applied to such problems which are too complex to be handled by traditional analytical methods, and gives good adaptibility for unpredictable environment. In this paper, the positions of the mobile robot are taken as the variables of the neural circuit and the differential equations are derived based on the performance index which is the weighted summation of the functions of the distances between the goal and current position of each robot, between each pair of robots and between the goal and current position of each robot, between each pair of robots and between obstacles and robots. Also is studied the problem of local minimum and of detour in large radius around obstacles, which is caused by inertia of mobile robots. To show the validity of the proposed method an example is illustrated by computer simulation, in which 6 mobile robots with mass and friction traverse in a workspace with 6 obstacles.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1128-1131
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• 1996

The collision-free path planning presented here uses linear parametric curve with one intermediate connection point between start and target points. The algorithm, in which connection point is organized in elliptic chord.(.theta., .delta.), maps objects in Euclidean Space into images in CPS through intersection check between path and obstacles a process defined as GM. Elliptic locus has special property that the total distance between focus points through a point on ellipse is the same regardless of .theta.. Hence by locating the start and target points to focus points of ellipse, and organizing connection point in elliptic coordinate, the .delta.-axis of CPS represents length of path. The GM of EWS requires calculation of interference in circumferential direction only. The procedures for GM is developed which include categorization of obstacles to reduce calculation amount. Simulations of GM of EWS, on a PC with Pentium/90MHz, is carried out to measure performance of algorithm and the results are reported on a table. The simulations are done for number of cases with different number of obstacles and location of start/target points.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2450-2452
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• 2004

Map building is essential to a mobile robot navigation system. Localization and path planning methods depend on map building strategies. A topological map is commonly constructed using the GVG(Generalized Voronoi Graph). The advantage of the GVG based topological map is compactness. But the GVG method have many difficulties because it consists of collision-free path. In this paper, we proposed an extended map building method, the AVG (Areal Voronoi Graph) based topological map. The AVG based topological map consists of collision-free area. This feature can improve map building, localization and path planning performance.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.951-957
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• 1988

A collision-free trajectory planning algorithm is proposed to optimally coordinate two robots working in a common 3-D workspace. Each link of the two robots is modeled as a line segment and by their motion priority, one of the two robots is chosen as the master and the other the slave. And the one-step-ahead minimum distance between the two robots is computed by moving the master to the next location on its specified trajectory. Then the nominal trajectory of the slave is modified such that the distance between the next locations of the master and the slave must be larger than a prespecified allowable minimum distance. Here the weighted sum of the trajectory error and the joint motions of the slave is minimized by using the linear programming technique under the constraints that joint angle and velocity limits are not violated. To show the validity of the proposed algorithm, a numerical example is illustrated by employing a two dof's and a three dof's planar robots.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.4
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• pp.28-34
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• 1998

This paper presents a new method for local obstacle avoidance of indoor mobile robots. The method combines a directional approach called the lane method and a velocity space approach. The lane method divides working area into lanes and then chooses the best lane to follow for efficient and collision-free movement. Then, the heading direction to enter and follow the best lane is decided, and translational and rotational velocity considering physical limitations of a mobile robot are determined. Since this method combines both the directional and velocity space method, it shows collision-free motion as well as smooth motion taking the dynamic of the robot into account.