• The Journal of Korea Robotics Society
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• v.16 no.3
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• pp.283-290
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• 2021

We propose a task and motion planning algorithm for clearing obstacles and wiping surfaces, which is essential for surface disinfection during the pathogen disinfection process. The proposed task and motion planning algorithm determines task parameters such as grasping pose and placement location during the planning process without using pre-specified or discretized values. Furthermore, to quickly inspect many unit motions, we propose a motion feasibility prediction algorithm consisting of collision checking and an SVM model for inverse mechanics and self-collision prediction. Planning time analysis shows that the feasibility prediction algorithm can significantly increase the planning speed and success rates in situations with multiple obstacles. Finally, we implemented a hierarchical control scheme to enable wiping motion while following a planner-generated joint trajectory. We verified our planning and control framework by conducted an obstacle-clearing and surface wiping experiment in a simulated disinfection environment.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.3
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• pp.281-287
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• 2023

Establishing a ship's passage plan is an essential step before it starts to sail. The research related to the automatic generation of ship passage plans is attracting attention because of the development of maritime autonomous surface ships. In coastal water navigation, the land, islands, and navigation rules need to be considered. From the path planning algorithm's perspective, a ship's passage planning is a global path-planning problem. Because conventional global path-planning methods such as Dijkstra and A^* are time-consuming owing to the processes such as environmental modeling, it is difficult to modify a ship's passage plan during a voyage. Therefore, the D^* algorithm was used to address these problems. The starting point was near Busan New Port, and the destination was Ulsan Port. The navigable area was designated based on a combination of the ship trajectory data and grid in the target area. The initial path plan generated using the D^* algorithm was analyzed with 33 waypoints and a total distance of 113.946 km. The final path plan was simplified using the Douglas-Peucker algorithm. It was analyzed with a total distance of 110.156 km and 10 waypoints. This is approximately 3.05% less than the total distance of the initial passage plan of the ship. This study demonstrated the feasibility of automatically generating a path plan in coastal navigation for maritime autonomous surface ships using the D^* algorithm. Using the shortest distance-based path planning algorithm, the ship's fuel consumption and sailing time can be minimized.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.405-408
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• 1991

In this paper, the algorithm of Resolved Motion Rate Control(RMRC) is applied to the robot manipulator to implement a desired straight trajectory in the cartesian space, PI controller is also used to control the velocity and position which are produced by RMRC algorithm. And Bounded Deviation Method is used to determine the intermediate knot points which satisfy a given tolerence limit, between the straight line segment.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.168-171
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• 1993

In this paper, we design a time optimal controller of a dual arm robot to handle the object. Differently from the master-slave type robot, same priority is imposed on the both of the arms for effective handling the specifed object. For finding a time optimal collision-free trajectory, a graphical method is applied for the robot with two degree of freedom. Some simulation results show the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1181-1184
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• 1996

As usual systems, robot manipulators have also physical constraints for operating. It is a difficult problem that we operate manipulator in the minimal time under these constraints. In this paper, we solve this problem dividing it into two steps. In the first step, we find the minimal time trajectories by optimizing qubic polynomial joint trajectories using evolutionary algorithms. In the second step, we optimize controller for robot manipulator to track precisely trajectories optimized in the previous step.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.144-148
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• 1989

We solve the inverse kinematics problems in robotics by employing a neural network. In the practical situation. it is not easy to obtain the exact inverse kinematics solution, since there are many unforeseen errors such as the shift of a robot base the link's bending, et c. Hence difficulties follow in the trajectory planning. With the neural network, it is possible to train the robot motion so that the robot follows the desired trajectory without errors even under the situation where the unexpected errors are involved. In this work, Back-Propagation rule is used as a learning method.

• The Journal of Korea Robotics Society
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• v.3 no.4
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• pp.338-344
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• 2008

Most omni-directional mobile robots have to change their trajectory for avoiding obstacles regardless of the size of the obstacles. However, an omni-directional mobile robot having kinematic redundancy can maintain the trajectory while the robot avoids small obstacles. This works deals with the kinematic modeling and motion planning of an omni-directional mobile robot with kinematic redundancy. This robot consists of three wheel mechanisms. Each wheel mechanism is modeled as having four joints, while only three joints are necessary for creating the omni-directional motion. Thus, each chain has one kinematic redundancy. Two types of wheel mechanisms are compared and its kinematic modeling is introduced. Finally, several motion planning algorithms using the kinematic redundancy are investigated. The usefulness of this robot is shown through experiment.

• Journal of the Ergonomics Society of Korea
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• v.6 no.1
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• pp.25-32
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• 1987

The paesent paper deals with obtaining the properly mixed application critaeia for the manual mode, using computer graphic simulation, in order to recover the error effectively occurring in the advanced teleoperator work of man-robot system. In these experiments the error which is occurred during performing the automatic mode is recovered by the manual mode which is combined properly the operation by hyman with the operation by control program. The result shows an improvement availibility of the system by not only establishing an efficient combination of the manual mode according to trajectory planning but also recovering the error effectively. Therefore we suggest that the operation by control program should be applied in macro motion of control and the operation by human in micro motion of control.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1581-1584
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• 1997

This paper poropsed an efficient optimization technuque to resolve redundancy and a trajectory planning for a high precision control using proposed optimization technique. The proposed techniqus is the joint disturbance torque optimizatioin considering redundancy in the joing servo control. Joint disturbance torque is not unknown it is described dynamic equation ignored friction and viscosity. The proposed technique is used the dynamic equatiion included the joint disturbance torque characteristics. Numerical example of 3 joint planar redundant robot manipulator is simulated. In the 2-norm minimization of joint disturbance torque we compared pseudoinverse local optimization with proposed technique, and the results showed better the proposed technique. So the proposed technique can be highly precision controlled redundant robot manipulators in the joint servo control.

• Journal of the Korean Society of Industry Convergence
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• v.19 no.4
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• pp.167-175
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• 2016

We present a method for improving adaptability of Learning from Demonstration (LfD) strategy by combining the LfD and Particle Swarm Optimization (PSO). A trajectory generated from an LfD is modified with PSO by minimizing a fitness function that considers constraints. Finally, the final trajectory is suitable for a task and adapted for constraints. The effectiveness of the method is shown with a target reaching task with a manipulator in three-dimensional space.