• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.990-995
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• 1990

A minimum-time trajectory planning for two robot arms with designated paths and coordination is proposed. The problem considered in this paper is a subproblem of hierarchically decomposed trajectory planning approach for multiple robots : i) path planning, ii) coordination planning, iii) velocity planning. In coordination planning stage, coordination space, a specific form of configuration space, is constructed to determine collision region and collision-free region, and a collision-free coordination curve (CFCC) passing collision-free region is selected. In velocity planning stage, normal dynamic equations of the robots, described by joint angles, velocities and accelerations, are converted into simpler forms which are described by traveling distance along collision-free coordination curve. By utilizing maximum allowable torques and joint velocity limits, admissible range of velocity and acceleration along CFCC is derived, and a minimum-time velocity planning is calculated in phase plane. Also the planning algorithm itself is converted to simple numerical iterative calculation form based on the concept of neural optimization network, which gives a feasible approximate solution to this planning problem. To show the usefulness of proposed method, an example of trajectory planning for 2 SCARA type robots in common workspace is illustrated.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2348-2350
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• 1998

The hybrid control system for a wheeled mobile robot with nonholonomic constraints to perform a cluttered environment maneuver is proposed. The proposed hybrid control system consists of a continuous state system for the trajectory control, a discrete state system for the motion and orientation control, and an interface control system for the interaction process between the continuous dynamics and the discrete dynamics The continuous control systems are modeled by the switched systems with the control of driving wheels, and the digital automata for motion control are modeled and implemented by the abstracted motion of mobile robot. The motion control tasks such as path generation, motion planning, and trajectory control for a cluttered environment are investigated as the applications by simulation studies.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.2
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• pp.170-177
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• 1993

In robotic arc welding, the roll (rotation) of the torch about its direction vector does not have any effect on the welding operation. Thus we could use this redundant degree of greedom for the motion control of the robot manipulator. This paper presents an algorithm for the pseudo- inverse kinematic motion control of the 6-axis robot, which utilizes the above mentioned redunancy. The prototype welding operation and the tool path are also graphically simulated. Since the proposed algorithm requires only the position and normal vector of the weldine as an input data, it is useful for the CAD-based off-line programming of the arc welding robot. In addition, it also has the advantages of the redundant manipulator motion control, like singularity avoidance and collision free motion planning, when compared with the other motion control method based on the direct inverse kinematics.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.7-10
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• 2007

This paper presents a fuzzy footstep planner for humanoid robots in complex environments. First, we define locomotion primitives for humanoid robots. A global planner finds a global path from a navigation map that is generated based on a combination of 2.5 dimensional maps of the 3D workspace. A local planner searches for an optimal sequence of locomotion primitives along the global path by using fuzzy footstep planning. We verify our approach on a virtual humanoid robot in a simulated environment. Simulation results show a reduction in planning time and the feasibility of the proposed method.

• Proceedings of the IEEK Conference
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• 2002.06e
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• pp.25-28
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• 2002

The path planning of autonomous mobile robot use two method. One is global path planning and another is local path planning. In this paper, We study the local path planning of autonomous mobile robot move in unknown enviroment. This local path planning is based on neural network using the direction indicator rules learning. also the system is made up of sensor system. The motion control system for real-time execution. The experimental results show that the developed direction indicator system operates properly and strongly at circumstance.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.4
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• pp.368-374
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• 2013

Maintenance works for current high-rise buildings significantly depend on human labor, unlike other construction processes that are gradually being automated. Herein, this paper proposes robotic building maintenance system using motion control, in specific, reducing a system jerk which is directly subjected to improve the process performance and economic feasibility. The sensor for detecting straight and curvature section of the building facade, moreover rail-joint segment can be detected and be utilized for reducing jerk of the system. Analysis of the proposed system error caused by excessive vibration, e.g. jerk motion is introduced. To enhance the stability and safety of the system, herein, the strategy is proposed for enhancing the performance of the system based on anti-jerk motion control algorithm which comes out increasing the stability and sustainability of the integrated system, as well.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.8
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• pp.1503-1517
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• 1994

Intelligent Motion Planning System(IMPS) is presented for a robot to achieve an efficient path toward the given target point in two dimensional unknown environment is constructed with unrestricted obstacle shapes. IMPS consists of three components for making intelligent motion. These components are real-time motion planning algorithm based on a discontinous boundary method, fuzzy neural network decision system for heuristic knowledge representation, and world modeling with forgetting and reinforcing memory cells. First of all, in real-time motion planning algorithm, the behavior-based architectural method is used to generate subgoal. A behavior generates a subgoal independently by using the method of discontinuous boundary in sensed area. The discontinuous boundary method is a new proposed fast obstacle avoidance algorithm. The second component is fuzzy neural network decision system for accomplishing the subgoal. The heuristic rules are imbedded on the fuzzy neural network to make an intelligent decision. The last one is a forgetting, reinforcing memory technique for the construction of external world map. The activation values of all activated memory cells in grid space are decreased monotonically and after all they are burned out. Therefore, after sufficient journey, robot can have a stationary world map even if the dynaic obstacles exist. Using the IMPS, several simulations show the efficient achievement of target point in unknown enviroment with obstcles of various shapes.

• The Journal of Korea Robotics Society
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• v.8 no.4
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• pp.292-297
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• 2013

This paper presents a new method of kinematic modeling for autonomous bicycle by using the differential motion transformation. Kinematic model is indispensable to trajectory planning and control for an autonomous mobile robot. The conventional methods of kinematic modeling for an autonomous bicycle depend on intuition by geometry. On the contrary, the proposed method in this paper is based on the systematic differential motion transformation, thus applicable to various types of autonomous bicycles. The differential motion transformation gives Jacobian between two coordinate frames and the velocity kinematics as a result.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.530-533
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• 1995

This paper deals with the problem of motion planning for a unicycle-like robot. We present a simple local planner for unicycle model, based on an approximation of the desired configuration generated by local holonomic planner that ignores motion constraints. To guarantee a collision avoidance, we propose an inequality constraint, based on the motion analysis with the constant control input and time interval. Consequently, we formulate our problem as the constrained optimization problem and a feedback scheme based on local sensor information is established by simply solving this problem. Through simulations, we confirm the validity and effectiveness of our algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.7
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• pp.586-593
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• 2000

In this paper we propose a new approach to the autonomous wall-following of wheeled mobile robots using hybrid system reference motion synthesis and generation. The hybrid system approach is in-troduced to the motion control of nonholonomic mobile robots for the indoor navigation problems. In the dis-crete event system the discrete states are defined by the user-defined constraints and the reference mo-tion commands are specified in the abstracted motions. The hybrid control system applied for the non-holonomic mobile robots can combine the motion planning and autonomous navigation with obstacle avoid-ance for the indoor navigation problem. Simulation results show that hybrid system approach is an effective method for the autonomous navigation in indoor environments.