• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.120.3-120
• /
• 2001

We propose a new method of path planning for cleaning robots. Path planning problem for cleaning robots is different from conventional path planning problems in which finding a collision-free trajectory from a start point to a goal point is focused. In the case of cleaning robots, however, a planned path should cover all area to be cleaned. To resolve this problem in a systematic way, we propose a method based on a graph model as follows: at first, partition a given map into proper regions, then transform a divided region to a vertex and a connectivity between regions to an edge of a graph. Finally, a region is divided into sub-regions so that the graph has a unary tree which is the simplest Hamilton path. The effectiveness of the proposed method is shown by computer simulation results.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
• /
• v.5B no.1
• /
• pp.63-69
• /
• 2005

The motion of animals and gymnasts in the air as well as free flying space robots without thrusters are subjected to nonholonomic constraints generated by the law of conservation of angular momentum. The purpose of this paper is to derive analytical posture control laws for free flying objects in the air. We propose the bang-bang control method for trajectory planning of a 3 link mechanical system with initial angular momentum. This technique is used to reduce the DOF (degrees of freedom) at first switching phase and to determine the control inputs to steer the reduced order system to the desired position. Computer simulations for motion planning of an athlete approximated by 3 link, namely platform diving, are provided to verify the effectiveness of the proposed control scheme.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10a
• /
• pp.133-136
• /
• 1996

The nozzle dam task is essentially needed to maintain and repair nuclear power plants. For this task, an 8-dof redundant robot is studied with a local path-planning method[l] which is effective to find the optimal joint path in the constrained environment. In this paper, the method[l] is improved practically with the weight matrix and efficient algorithm to find working set. The effectiveness of the proposed method is demonstrated by simulation and animation.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.2
• /
• pp.115-120
• /
• 2015

Recently, in automotive technology area, intelligent safety systems have been actively accomplished for drivers, passengers, and pedestrians. Also, many researches are focused on development of autonomous vehicles. This paper propose the application of LiDAR sensors, which takes major role in perceiving environment, terrain classification, obstacle data clustering method, and local map building for autonomous driving. Finally, based on these results, planning for lane change path that vehicle tracking possible were created and the reliability of path generation were experimented.

• Journal of Drive and Control
• /
• v.21 no.1
• /
• pp.46-52
• /
• 2024

The advancement of autonomous driving technology has heightened the importance of Autonomous Mobile Robotics (AMR) within smart factories. Notably, in tasks involving the transportation of heavy objects, the consideration of weight in route optimization and path planning has become crucial. There is ongoing research on local path planning, such as Dijkstra, A^*, and RRT^*, focusing on minimizing travel time and distance within smart factory warehouses. Additionally, there are ongoing simultaneous studies on route optimization, including TSP algorithms for various path explorations and on minimizing energy consumption in mobile robotics operations. However, previous studies have often overlooked the weight of the objects being transported, emphasizing only minimal travel time or distance. Therefore, this research proposes route planning that accounts for the maximum payload capacity of mobile robotics and offers load-optimized path planning for multi-destination transportation. Considering the load, a genetic algorithm with the objectives of minimizing both travel time and distance, as well as energy consumption is employed. This approach is expected to enhance the efficiency of mobility within smart factories.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.8
• /
• pp.1483-1490
• /
• 2009

This parer is presented multiple path-planning of unmanned autonomous forklift using modified genetic algorithm and fuzzy inference system. There are a task-level feedback method and a method that path is dynamically replaned in realtime while the autonomous vehicles are moving by means of an optimal algorithm for existing multiple path-planning. However, such methods cause malfunctions and inefficiency in the sense of time and energy, and path-planning should be dynamically replanned in realtime. To solve these problems, we propose multiple path-planning using modified genetic algorithm and fuzzy inference system and show the performance with autonomous vehicles. For experiment, we designed and built two autonomous mobile vehicles that equipped with the same driving control part used in actual autonomous forklift, and test the proposed multiple path-planning algorithm. Experimental result that actual autonomous mobile vehicle, we verified that fast optimized path-planning and efficient collision avoidance are possible.

• 제어로봇시스템학회:학술대회논문집
• /
• 1987.10b
• /
• pp.58-62
• /
• 1987

In this paper, path planning, modelling, and control of manipulators are described. The path planning deals with specifying how to define the motion of hand along straight line paths in the minimum amount of time. A new model was developed for the manipulator, which is based on the classical equations of motion of a rigid body. A new control algorithm was developed which controls the manipulator in terms of the position and orientation of the hand.

• Proceedings of the KSME Conference
• /
• 2004.11a
• /
• pp.766-771
• /
• 2004

In this paper, new exploration mobile robot is presented. This mobile robot, called Robhaz-6W, is able to overcome hazardous terrains, recognize three dimensional terrain information and generate a path toward the destination by itself. We develop the passive four bar linkage mechanism adoptable to such terrain without any active control and the real time stereo vision system for obstacle avoidance, a remote control and a path planning method. And the geometrical information is transmitted to the operator in the remote site via wireless LAN equipment. And finally, experimental results for the passive mechanism, the real time stereo vision system, the path planning are reported, which show the versatility of the proposed mobile robot system to carry out some tasks.

• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.9
• /
• pp.891-897
• /
• 2010

This paper proposes a cooperative control algorithm for a dual-arms robot which is carrying an object to the desired location. When the dual-arms robot is carrying an object from the start to the goal point, the optimal path in terms of safety, energy, and time needs to be selected among the numerous possible paths. In order to quantify the carrying efficiency of dual-arms, DAMM (Dual Arm Manipulability Measure) has been defined and applied for the decision of the optimal path. The DAMM is defined as the intersection of the manipulability ellipsoids of the dual-arms, while the manipulability measure indicates a relationship between the joint velocity and the Cartesian velocity for each arm. The cost function for achieving the optimal path is defined as the summation of the distance to the goal and inverse of this DAMM, which aims to generate the efficient motion to the goal. It is confirmed that the optimal path planning keeps higher manipulability through the short distance path by using computer simulation. To show the effectiveness of this cooperative control algorithm experimentally, a 5-DOF dual-arm robot with distributed controllers for synchronization control has been developed and used for the experiments.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.7
• /
• pp.4482-4488
• /
• 2014

This paper proposes the creation scheme of a threat map for robot global path planning. The threat map was generated using neural network theory by analyzing the robot's armament state and the menace information of an enemy or obstacle. In addition, the performance of the suggested method was verified using the compared result of the damage amount and existing robot path data.