• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.40-43
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• 1996

An off-line programming, OLP, system is widely used in automation fines. To help an on-line robot system to carry out desirable tasks planned by the off-line simulation, an approach to the real-time communication is presented. The OLP system developed consists of a software, a host computer(PC), a SCARA robot body, four servo drivers, and four independent joint controllers. This study focuses on the software where real-time communication is included. The software, can be used in teaching, trajectory planning, real-time running, and performance evaluation. The evaluation of different control algorithms is one of the merits of the software. The software can give servo commands for task running. A comparison of generated and corresponding actual trajectories provides the evaluation of task performance. The safety, of the OLP system is ensured by alarming malfuntions of the system. The OLP system developed can reduce the teaching time and increase the user's convenience.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.5
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• pp.357-368
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• 1991

Collision-free trajectory planning for two robots is considered. The two robot system handled in the paper is given specified geometric paths for two robots, and the task is repeating. Then, the robot dynamics is transformed as a function of the traveled lengths along the paths, and the bounds on acceleration and velocity are described in the phase plane be taking the constraints on torques and joint velocities into consideration. Collision avoidance and time optimality are considered simultaneously in the coordination space and the phase plane, respectively. The proof for the optimality of the proposed algorithm is given, and a simulation result is included to show the usefulness of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.111-119
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• 1996

In this paper, we propose time-optimal trajectory planning algorithms for cooperative multi-robot manipulators system considering optimal load distribution. Internal forces essentially effect on time optimal trajectory planning and if they are comitted, the time optimal scheme is not no longer true. Therefore, we try to find the internal force factors of cooperative robot manipulators system in a time-optimal aspect. In this approach, a specific generalized inverse is used and is fuzzified for the purpose. In this optimal method, the fuzzy logic concept is used and selected for diminishing computation time, for finding the load distribution factors.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.9 no.6
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• pp.87-94
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• 2010

In this paper, a new simulator of the biped robot for planning walking patterns was showed. And this simulator(MHBiped) is able to not only visualize the plan of patterns but also verify whether a biped robot design is suitable. In addition, MHBipd can modify various kinds of walking parameters and the trajectory of biped robot. Therefore, a new biped robot can be designed easily by the this simulator before you apply to a robot. As a result, a well-balanced parameters of walking patterns watching the movement of CG and ZMP can be obtained. Walking patterns should be changed according to both the existence of obstacles and conditions of ground and it can be described by the trajectory of hip and ankles. All those trajectorys can be also obtained by the cubic spline functions and the way of modeling walking patterns. The results of simulator, the movement function of CG and ZMP, the cubic spline functions and modeling of biped robot were introduced in this paper. And the effectiveness of this simulator was confirmed by the simulations.

• The Journal of Korea Robotics Society
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• v.7 no.2
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• pp.150-159
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• 2012

In this paper, we propose a cost-aware Rapidly-exploring Random Tree (RRT) path planning algorithm for mobile robots. A mobile robot is presented with a cost map of the field of interest and assigned to move from one location to another. As a robot moves, the robot is penalized by the cost at its current location according to the cost map. The overall cost of the robot is determined by the trajectory of the robot. The goal of the proposed cost-aware RRT algorithm is to find a trajectory with the minimal cost. The cost map of the field can represent environmental parameters, such as temperature, humidity, chemical concentration, wireless signal strength, and stealthiness. For example, if the cost map represents packet drop rates at different locations, the minimum cost path between two locations is the path with the best possible communication, which is desirable when a robot operates under the environment with weak wireless signals. The proposed cost-aware RRT algorithm extends the basic RRT algorithm by considering the cost map when extending a motion segment. We show that the proposed algorithm gives an outstanding performance compared to the basic RRT method. We also demonstrate that the use of rejection sampling can give better results through extensive simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2237-2242
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• 2005

The original RRT is iteratively expanded by applying control inputs that drive the system slightly toward randomly-selected states, as opposed to requiring point-to-point convergence, as in the probabilistic roadmap approach. It is generally known that the performance of RRTs can be improved depending on the selection of the metrics in choosing the nearest vertex and bias techniques in choosing random states. We designed a path planning algorithm based on the RRT method for a remote-controlled mobile robot. First, we considered a bias technique that is goal-biased Gaussian random distribution along the command directions. Secondly, we selected the metric based on a weighted Euclidean distance of random states and a weighted distance from the goal region. It can save the effort to explore the unnecessary regions and help the mobile robot to find a feasible trajectory as fast as possible. Finally, the constraints of the actuator should be considered to apply the algorithm to physical mobile robots, so we select control inputs distributed with commanded inputs and constrained by the maximum rate of input change instead of random inputs. Simulation results demonstrate that the proposed algorithm is significantly more efficient for planning than a basic RRT planner. It reduces the computational time needed to find a feasible trajectory and can be practically implemented in a remote-controlled mobile robot.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.2
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• pp.568-579
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• 1995

An off-line programming (OLP) system was proposed and developed in order to save cost and time in adjusting a robot to new workcells or applying new algorithms to actual trajectory planning. The developed OLP system was especially designed to be operated in a PC level host computer. A SCARA robot with four axes was selected as an objective robot. The OLP system developed in this study consisted of such modules as data base, three-dimensional graphics, kinematics, trajectory planning, dynamics, control, and commands. Each module was constructed to form an independent unit so that it can be easily modified or improved. The OLP system was programmed for a graphic user interface in Borland $C^{++}$ language. Some of system operating commands and an interpreter were devised and used for more convenient programming of robot simulations.s.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.3
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• pp.206-212
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• 2009

This paper presents an optimized integrated task planning and control approach for manipulating a nonholonomic robot by mobile manipulators. Then, we derive a kinematics model and a mobility of the mobile manipulator(M2) platform considering it as the combined system of the manipulator and the mobile robot. to improve task execution efficiency utilizing the redundancy, optimal trajectory of the mobile manipulator(M2) platform are maintained while it is moving to a new task point. A cost function for optimality can be defined as a combination of the square errors of the desired and actual configurations of the mobile robot and of the task robot. In the combination of the two square errors, a newly defined mobility of a mobile robot is utilized as a weighting index. With the aid of the gradient method, the cost function is minimized, so the path trajectory that the M2 platform generates is optimized. The simulation results of the 2 ink planar nonholonomic M2 platform are given to show the effectiveness of the proposed algorithm.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.8
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• pp.585-593
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• 2004

Fault-tolerant gait planning in legged locomotion is to design gaits with which legged robots can maintain static stability and motion continuity against a failure in a leg. For planning a robust and deadlock-free fault-tolerant gait, kinematic constraints caused by a failed leg should be closely examined with respect to remaining mobility of the leg. In this paper, based on the authors's previous results, deadlock avoidance scheme for fault-tolerant gait planning is proposed for a hexapod robot walking over even terrain. The considered fault is a locked joint failure, which prevents a joint of a leg from moving and makes it locked in a known position. It is shown that for guaranteeing the existence of the previously proposed fault-tolerant tripod gait of a hexapod robot, the configuration of the failed leg must be within a range of kinematic constraints. Then, for coping with failure situations where the existence condition is not satisfied, the previous fault-tolerant tripod gait is improved by including the adjustment of the foot trajectory. The foot trajectory adjustment procedure is analytically derived to show that it can help the fault-tolerant gait avoid deadlock resulting from the kinematic constraint and does not make any harmful effect on gait mobility. The post-failure walking problem of a hexapod robot with the normal tripod gait is addressed as a case study to show the effectiveness of the proposed scheme.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.3 s.303
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• pp.1-10
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• 2005

This paper proposes a novel fault-tolerant gait planning of a hexapod robot considering kinematic constraints. The failure concerned in this paper is a locked joint failure for which a joint in a leg cannot move and is locked in place. It is shown that the conventional fault-tolerant gait of a hexapod robot for forward walking on even terrain may be fallen into deadlock, depending on the configuration of the failed leg. For coping with such deadlock situation, a novel fault-tolerant gait planning is proposed. It can avoid deadlock by adjusting the position of the foot trajectory, and has the same leg sequence and stride length as those of the conventional fault-tolerant gait. To demonstrate the superiority of the proposed scheme, a case study is presented in which a hexapod robot, having walked over even terrain before a locked joint failure, could avoid deadlock and continue its walking by the proposed fault-tolerant gait planning.