• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.1
• /
• pp.53-60
• /
• 2010

We propose a motion planning method for autonomous mobile robots. In order to minimize traveling time, a smooth path and a time optimal velocity profile should be generated under kinematic and dynamic constraints. In this paper, we develop an effective and practical method to generate a good solution with lower computation time. The initial path is obtained from voronoi diagram by Dijkstra's algorithm. Then the path is improved by changing the graph and path simultaneously. We apply the dynamic programming algorithm into the stage of improvement. Simulation results are presented to verify the performance of the proposed method.

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

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.15 no.2
• /
• pp.515-522
• /
• 1991

Determining the motion using optimal technique about traveling time and trajectory planning has been studied often in recent years, but the study of determining the optimal robot dimensions is rare, the authors attempt to find out the least driving torques and energy as the optimization of link length ratio referred to 2R SCARA and 3R robot manipulators. For the given linear path with triangular velocity profile, the inverse kinematic and dynamic problems are examined in order to lead into solution of problem, which is suggested for optimal design of link lengths. Accordingly, optimal link length ratio is obtained with respect to each case.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.29B no.10
• /
• pp.27-36
• /
• 1992

This paper proposes a numerical method of motion planning for manipulators using Foruier series. For a redundant manipulator, we predetermine the trajectories of redundant joints in terms of the Nth partial sum of the fourier series. then the optimal coefficients of the fourier series are searched by the Powell's method. For a nonredundant or redundant manipulator, CS02T-continuous smooth joint trajectory for a point-to-point task can be obtained while considering the frequency response. We apply the proposed method to the 3-link planar manipulator and the PUMA 560 manipulator. To show the validity of the proposed method, we analyze solutions by the Fast Fourier Transform (FFT). Also, several features are discussed to obtain an optimal solution.

• The Journal of Korea Robotics Society
• /
• v.16 no.2
• /
• pp.122-129
• /
• 2021

For the Simultaneous Localization and Mapping (SLAM) problem, a different path results in different SLAM results. Usually, SLAM follows a trail of input data. Active SLAM, which determines where to sense for the next step, can suggest a better path for a better SLAM result during the data acquisition step. In this paper, we will use reinforcement learning to find where to perceive. By assigning entire target area coverage to a goal and uncertainty as a negative reward, the reinforcement learning network finds an optimal path to minimize trajectory uncertainty and maximize map coverage. However, most active SLAM researches are performed in indoor or aerial environments where robots can move in every direction. In the urban environment, vehicles only can move following road structure and traffic rules. Graph structure can efficiently express road environment, considering crossroads and streets as nodes and edges, respectively. In this paper, we propose a novel method to find optimal SLAM path using graph structure and reinforcement learning technique.

• Journal of the Korean Society of Industry Convergence
• /
• v.21 no.3
• /
• pp.125-131
• /
• 2018

In this paper, we propose a homogeneous multisensor-based navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments with moving obstacles using multi-ultrasonic sensor. Instead of using "sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data, "command fusion" method by fuzzy inference is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor using fuzzy inference is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we performed simulations in PC as well as real experiments with mobile robot, AmigoBot. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.1046-1051
• /
• 1991

For the conveyor tracking application of a robot manipulator, a new control scheme is presented. The presented scheme is divided into two stages : the upper one is the motion planning stage and the lower one is the motion control stage. In the upper stage, the nominal trajectory which tracks the part moving in a constant velocity, is planned considering the robot arm dynamics. On the other hand, in the lower level, the perturbed trajectory is generated to track the variation in the velocity of conveyor belt via sensory feedback and the perturbed arm dynamics. In both stages, the conveyor tracking problem is formulated as an optimal tracking problem, and the torque constraints of a robot manipulator are taken into account. Simulation results are then presented and discussed.

• Journal of Astronomy and Space Sciences
• /
• v.25 no.4
• /
• pp.361-374
• /
• 2008

Recently, satellite formation flying has been a topic of significant research interest in aerospace society because it provides potential benefits compared to a large spacecraft. Some techniques have been proposed to design optimal formation trajectories minimizing fuel consumption in the process of formation configuration or reconfiguration. In this study, a method is introduced to build fuel-optimal trajectories minimizing a cost function that combines the total fuel consumption of all satellites and assignment of fuel consumption rate for each satellite. This approach is based on collocation and nonlinear programming to solve constraints for collision avoidance and the final configuration. New constraints of nonlinear equality or inequality are derived for final configuration, and nonlinear inequality constraints are established for collision avoidance. The final configuration constraints are that three or more satellites should form a projected circular orbit and make an equilateral polygon in the horizontal plane. Example scenarios, including these constraints and the cost function, are simulated by the method to generate optimal trajectories for the formation configuration and reconfiguration of multiple satellites.

• Proceedings of the Korean Society Of Semiconductor Equipment Technology
• /
• 2005.09a
• /
• pp.110-123
• /
• 2005

This paper proposes an intelligent method for the optimal load distribution of two cooperating robots(TCRs) using fuzzy logic. The proposed scheme requires the knowledge of the robots' dynamics, which in turn depend upon the characteristics of large flat panel displays(LFPDs) carried by the TCRs. However, the dynamic properties of the LFPD are not known exactly, so that the dynamics of the robots, and hence the required joint torque, must be calculated for nominal set of the LFPD characteristics. The force of the TCRs is an important factor in carrying the LFPD. It is divided into external force and internal force. In general , the effects of the internal force of the TCRs are not considered in performing the load distribution in terms of optimal time, but they are essential in optimal trajectory planning: if they are not taken into consideration, the optimal scheme is no longer fitting. To alleviate this deficiency, we present an algorithm for finding the internal-force factors for the TCRs in terms of optimal time. The effectiveness of the proposed system is demonstrated by computer simulations using two three-joint planner robot manipulators.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.5
• /
• pp.405-411
• /
• 2011

This paper presents a hierarchical trajectory planning method which can handle a collision-free of the planned path in complex and dynamic environments. A PV (Path & Velocity profile) planning method minimizes a sharp change of orientation and waiting time to avoid a collision with moving obstacle through detour path. The path generation problem is solved by three steps. In the first step, a smooth global path is generated using $A^*$ algorithm. The second step sets up the velocity profile for the optimization problem considering the maximum velocity and acceleration. In the third step, the velocity profile for obtaining the shortest path is optimized using the fuzzy and genetic algorithm. To show the validity and effectiveness of the proposed method, realistic simulations are performed.