• Proceedings of the Korea Multimedia Society Conference
• /
• 2001.11a
• /
• pp.890-895
• /
• 2001

In this paper, we address on the problem of automatic scheduling and motion generation of multiple mobile robots fur collecting material parts. We propose a model and so]union algorithm for the system. The formulated problem is divided into two kinds of problems; assignment problem and planning problem of robot motion. In this paper, several approaches to solution methods are presented and compared through computer simulation.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39C no.4
• /
• pp.400-406
• /
• 2014

In this paper, we propose an approach to minimizing total power consumption by deploying multiple clean-up robots simultaneously in a given area. For this, we propose to use the cooperative game theoretic approaches (i.e., Nash bargaining solution (NBS)) such that the robots can optimally and fairly negotiate the area division based on available resources and characteristics of the area, thereby leading to the minimum total power consumption. We define a utility function that includes power consumptions for characteristics of areas and the robots can agree on a utility pair based on the NBS. Simulation results show that the proposed approach can reduce the total average power consumption by 15-30% compared to a random area division approach.

• Proceedings of the KSME Conference
• /
• 2005.11a
• /
• pp.202.1-202.1
• /
• 2005

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2013.05a
• /
• pp.431-432
• /
• 2013

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.37.2-37
• /
• 2002

1. Introduction 2. Problem Formulation 3. Avoidability Measure And Relative Distance 4. Artificial Potential Field in Terms of Relative Distance 5. Simulation Results 6. Conclusions 7. Reference

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.147-151
• /
• 1991

In this paper a time-optimal path planning scheme for the multiple robot manipulators will be proposed by using hopfield neural network. The time-optimal path planning, which can allow multiple robot system to perform the demanded tasks with a minimum execution time and collision avoidance, may be of consequence to improve the productivity. But most of the methods proposed till now suffers from a significant computational burden and thus limits the on-line application. One way to avoid such a difficulty is to rearrange the problem as MTSP(Multiple Travelling Salesmen Problem) and then apply the Hopfield network technique, which can allow the parallel computation, to the minimum time problem. This paper proposes an approach for solving the time-optimal path planning of the multiple robots by using Hopfield neural network. The effectiveness of the proposed method is demonstrated by computer simulation.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.15 no.4
• /
• pp.406-411
• /
• 2005

In this paper, we present the area-based Q-learning to search a target object using multiple robot. To search the target in Markovian space, the robots should recognize their surrounding at where they are located and generate some rules to act upon by themselves. Under area-based Q-learning, a robot, first of all, obtains 6-distances from itself to environment by infrared sensor which are hexagonally allocated around itself. Second, it calculates 6-areas with those distances then take an action, i.e., turn and move toward where the widest space will be guaranteed. After the action is taken, the value of Q will be updated by relative formula at the state. We set up an experimental environment with five small mobile robots, obstacles, and a target object, and tried to search for a target object while navigating in a unknown hallway where some obstacles were placed. In the end of this paper, we presents the results of three algorithms - a random search, area-based action making (ABAM), and hexagonal area-based Q-teaming.

• Journal of Convergence for Information Technology
• /
• v.7 no.6
• /
• pp.181-186
• /
• 2017

In recent years, robots have been actively used for children's creativity learning and play, but most robots have a stereotyped form and have a high dependency on the program, making it difficult to learn creativity and play. In order to compensate for these drawbacks, We have created a robot that can easily and reliably combine each other. The robot can memorize the desired operation and execute the memorized operation by using one button. Also, in case multiple modules are combined, pressing the button once on any module makes it possible to easily adjust the operation of all the combined modules. In order to verify the actual operation, two, three, and five modules are combined to demonstrate the usefulness of the proposed structure and algorithm by implementing a gobbling motion and a walking robot. It is required to study intelligent modular robots that can control over the Internet by supplementing the wireless connection method.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.3
• /
• pp.236-241
• /
• 2015

This paper presents a study on transformable multiple quadruped robots by docking between robots and waist joints. This robot is able to go on a variety of angles because of mecanum wheels. It is also a hybrid design which allows robot use legs to overcome obstacles on complex terrains and wheels to move on flat ground. The robot is applied kinematics of mecanum wheels and walking, and its walking is based on specific patterns. Docking module is located in front and backside of robot, docking algorithm is suggested and fulfilled for docking between 2 robots. A waist joint is at the center of robot body for transformation and after docking and transformation, robot can activate new functions that carry something.

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