• Journal of Advanced Marine Engineering and Technology
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• v.27 no.4
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• pp.526-534
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• 2003

Motions of animals and gymnasts in the air as well as free flying space robots without thruster are subject to nonholonomic constraints generated by the law of conservation of angular momentum. The interest in nonholonomic control problems is motivated by the fact that such systems can not stabilized to its equilibrium points by the smooth control input. The purpose of this paper is to derive analytical posture control laws for free flying objects in the air. We propose a control method using bang-bang control for trajectory planning of a 3 link mechanical system with initial angular momentum. We reduce the DOF (degrees of freedom) of control object in the first control phase and determine the control inputs to steer the reduced order system from its initial position to its desired position. Computer simulation for a motion planning of an athlete approximated by 3 link is presented to illustrate the effectiveness of the Proposed control scheme.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.1
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• pp.63-69
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• 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
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• 2001.10a
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• pp.120.3-120
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• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.217-225
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• 2016

In this paper, we propose an improved path planning method and obstacle avoidance algorithm for two-wheel mobile robots, which can be effectively applied in an environment where obstacles can be represented by circles. Firstly, we briefly introduce the rapidly exploring random tree (RRT) and single polar polynomial (SPP) algorithm. Secondly, we present additional two methods for applying our proposed method. Thirdly, we propose a global path planning, smoothing and obstacle avoidance method that combines the RRT and SPP algorithms. Finally, we present a simulation using our proposed method and check the feasibility. This shows that proposed method is better than existing methods in terms of the optimality of the trajectory and the satisfaction of the kinematic constraints.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2769-2771
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• 2000

In this paper we propose new algorithms of path planning and obstacle avoidance for an autonomous mobile robot with vision system. Distance variation is included in path planning to approach the target point and avoid obstacles well. The fuzzy rules are also applied to both trajectory planning and obstacle avoidance to improve the autonomy of mobile robot. It is shown by computer simulation that the proposed algorithm is working well.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2417-2419
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• 2001

A path planning is one of the main subjects in a mobile robot. It is divided into two parts. One is a global path planning and another is a local path planning. This paper, using the formal two methods, presents that the mobile robot moves to multi-targets with avoiding unknown obstacles. For the shortest time and the lowest cost, the mobile robot has to find a optimal path between targets. To find a optimal global path, we used GA(Genetic Algorithm) that has advantage of optimization. After finding the global path, the mobile robot has to move toward targets without a collision. FLC(Fuzzy Logic Controller) is used for local path planning. FLC decides where and how faster the mobile robot moves. The validity of the study that searches the shortest global path using GA in multi targets and moves to targets without a collision using FLC, is verified by simulations.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.1
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• pp.78-86
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• 1998

This paper presents a numerical method of the minimum-time trajectory planning for a robot manipulator amid obstacles. Each joint displacement is represented by the linear combination of the finite-term quintic B-splines which are the known functions of the path parameter. The time is represented by the linear function of the same path parameter. Since the geometric path is not fixed and the time is linear to the path parameter, the coefficients of the splines and the time-scale factor span a finite-dimensional vector space, a point in which uniquely represents the manipulator motion. The displacement, the velocity and the acceleration conditions at the starting and the goal positions are transformed into the linear equality constraints on the coefficients of the splines, which reduce the dimension of the vector space. The optimization is performed in the reduced vector space using nonlinear programming. The total moving time is the main performance index which should be minimized. The constraints on the actuator forces and that of the obstacle-avoidance, together with sufficiently large weighting coefficients, are included in the augmented performance index. In the numerical implementation, the minimum-time motion is obtained for a planar 3-1ink manipulator amid several rectangular obstacles without simplifying any dynamic or geometric models.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2360-2362
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• 1998

This paper presents a new collison-free trajectory problem for SCARA robot manipulator. we use artificial potential field for collison detection and avoidance. The potential function is typically defined as the sum of attractive potential pulling the robot toward the goal configuration and a repulsive potential pushing the robot away from the obstacles. In here, end-effector of manipulator is represented as a particle in configuration space and moving obstacles is simply represented, too. we consider not fixed obstacle but moving obstacle in random. So, we propose new distance function of artificial potential field with moving obstacle for SCARA robot. At every sampling time, the artificial potential field is update and the force driving manipulator is derived from the gradient vector of artificial potential field. To real-time path planning, we apply very simple modeling to obstacle. Some simulation results show the effectiveness of the proposed approach.

• The Journal of Korea Robotics Society
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• v.17 no.4
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• pp.500-507
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• 2022

In this study, a motion planning method based on the integer representation of contact status between wheels and the ground is proposed for planning swing motion of a 6×6 wheel-legged robot to cross large obstacles and gaps. Wheel-legged robots can drive on a flat road by wheels and overcome large obstacles by legs. Autonomously crossing large obstacles requires the robot to perform complex motion planning of multi-contacts and wheel-rolling at the same time. The lift-off and touch-down status of wheels and the trajectories of legs should be carefully planned to avoid collision between the robot body and the obstacle. To address this issue, we propose a planning method for swing motion of robot legs. It combines an integer representation of discrete contact status and a trajectory optimization based on the direct collocation method, which results in a mixed-integer nonlinear programming (MINLP) problem. The planned motion is used to control the joint angles of the articulated legs. The proposed method is verified by the MuJoCo simulation and shows that over 95% and 83% success rate when the height of vertical obstacles and the length of gaps are equal to or less than 1.68 times of the wheel radius and 1.44 times of the wheel diameter, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.265-276
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• 2017

In this paper, a robust and more accurate trajectory tracking control method for a mobile robot is proposed using WIPDC(Weighted Integral Parallel Distributed Compensation) and T-S Fuzzy disturbance observer. WIPDC reduces the steady state error by adding weighted integral term to PDC. And, T-S Fuzzy disturbance observer makes it possible to estimate and cancel disturbances for a T-S fuzzy model system. As a result, the trajectory tracking controller based on T-S Fuzzy disturbance observer shows robust tracking performance. When the initial postures of a mobile robot and the reference trajectory are different, the initial control inputs to the mobile robot become too large to apply them practically. In this study, also, the problem is solved by designing an initial approach path using a path planning method which employs $B\acute{e}zier$ curve with acceleration limits. Performances of the proposed method are proved from the simulation results.