• Journal of the Korean Institute of Intelligent Systems
• /
• v.24 no.2
• /
• pp.179-185
• /
• 2014

In this paper, a quadruped walking pet robot for human-robot interaction, a robot-controller using a smart phone application program, and a home smart control system using sensor informations providing from the robot are described. The robot has 20 degree of freedom and consists of various sensors such as Kinect sensor, infrared sensor, 3 axis motion sensor, temperature/humidity sensor, gas sensor and graphic LCD module. We propose algorithms for the robot entertainment: walking algorithm of the robot, motion and voice recognition algorithm using Kinect sensor. emotional expression algorithm, smart phone application algorithm for a remote control of the robot, and home smart control algorithm for controlling home appliances. The experiments of this paper show that the proposed algorithms applied to the pet robot, smart phone, and computer are well operated.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.20 no.3
• /
• pp.441-446
• /
• 2010

Each robot decides and behaviors themselves surrounding circumstances in the swarm robot system. Robots have to conduct tasks allowed through cooperation with other robots. Therefore each robot should have the ability to learn and evolve in order to adapt to a changing environment. In this paper, we proposed learning based on Q-learning algorithm and evolutionary using Harmony Search algorithm and are trying to improve the accuracy using Harmony Search Algorithm, not the Genetic Algorithm. We verify that swarm robot has improved the ability to perform the task.

• Journal of the Korean Society for Precision Engineering
• /
• v.17 no.7
• /
• pp.113-123
• /
• 2000

In the navigation for a mobile robot, the collision avoidance with unexpected obstacles is essential for the safe navigation and it is independent of the technique used to control the mobile robot. This paper presents a new collision avoidance algorithm using neural network for the safe navigation of the autonomous mobile robot equipped with CAN and ultrasonic sensors. A tracked wheeled mobile robot has a stability and an efficiency to move on a rough ground. And its mechanism is simple. However it has difficulties to recognize its surroundings. Because the shape of the tracked wheeled mobile robot is a square type, sensor modules are generally located on the each plane surface of 4 sides only. In this paper, the algorithm using neural network is proposed in order to avoid unexpected obstacles. The important character of the proposed algorithm is to be able to detect the distance and the angle of inclination of obstacles. Only using datum of the distance and the angle, informations about the location and shape of obstacles are obtained, and then the driving direction is changed. Consequently, this algorithm is capable of real time processing and available for a mobile robot which has few sensor modules or the limited sensing range such as a tracked wheeled mobile robot. Effectiveness of the proposed algorithm is illustrated through a computer simulation and an experiment using a real robot.

• Journal of Institute of Control, Robotics and Systems
• /
• v.15 no.5
• /
• pp.538-542
• /
• 2009

Industrial manipulators have been mostly used in large companies such as automakers and electronics companies. In recent years, however, demands for industrial manipulators from small and medium-sized enterprises are on the increase because of shortage of manpower and high wages. Since these companies cannot hire robot engineers for operation and programming of a robot, intuitive teaching and playback techniques of a robot manipulator should replace the robot programming which requires substantial knowledge of a robot. This paper proposes an intuitive teaching and playback algorithm used in assembly tasks. An operator can directly teach the robot by grasping the end-effector and moving it to the desired point in the teaching phase. The 6 axis force/torque sensor attached to the manipulator end-effector is used to sense the human intention in teaching the robot. After this teaching phase, a robot can track the target position or trajectory accurately in the playback phase. When the robot contacts the environment during the teaching and playback phases, impedance control is conducted to make the contact task stable. Peg-in-hole experiments are selected to validate the proposed algorithm since this task can describe the important features of various assembly tasks which require both accurate position and force control. It is shown that the proposed teaching and playback algorithm provides high positioning accuracy and stable contact tasks.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2015.10a
• /
• pp.1350-1353
• /
• 2015

In this paper, we have researched about how to detect the fish robot objects in aquarium. We had used designed fish robots DOMI ver1.0, which had researched and developed for aquarium underwater robot. The model of the robot fish is analysis to maximize the momentum of the robot fish and the body of the robot is designed through the analysis of the biological fish swimming. We are planned to non-external equipment to find the position and manipulated the position using creating boundary to fish robot to detect the fish robot objects. Also, we focused the detecting fish robot in aquarium by using boundary algorithm. In order to the find the object boundary, it is filtering the video frame to picture frames and changing the RGB to gray. Then, applied the boundary algorithm stand of equations which operates the boundary for objects. We called these procedures is kind of image processing that can distinguish the objects and background in the captured video frames. It was confirmed that excellent performance in the field test such as filtering image, object detecting and boundary algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.10
• /
• pp.3373-3389
• /
• 2022

Exploration of mobile robot without prior data about environments is a fundamental problem during the SLAM processes. In this work, we propose improved version of previous Rmap algorithm by modifying its Exploration submodule. Despite the previous Rmap's performance which significantly reduces the overhead of the grid map, its exploration module costs a lot because of its rectangle following algorithm. To prevent that, we propose a new Rmap+ algorithm for autonomous path planning of mobile robot to explore an unknown environment. The algorithm bases on paired frontiers. To navigate and extend an exploration area of mobile robot, the Rmap+ utilizes the inner and outer frontiers. In each exploration round, the mobile robot using the sensor range determines the frontiers. Then robot periodically changes the range of sensor and generates inner pairs of frontiers. After calculating the length of each frontiers' and its corresponding pairs, the Rmap+ selects the goal point to navigate the robot. The experimental results represent efficiency and applicability on exploration time and distance, i.e., to complete the whole exploration, the path distance decreased from 15% to 69%, as well as the robot decreased the time consumption from 12% to 86% than previous algorithms.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.2492-2497
• /
• 2003

This paper presents optimal walking trajectory generation for a quadruped robot with genetic-fuzzy algorithm. In order to move a quadruped robot smoothly, both generations of optimal leg trajectory and free walking are required. Generally, making free walking is difficult to realize for a quadruped robot, because the patterned trajectory may interfere in the free walking. In this paper, we suggest the generation method for the leg trajectory satisfied with free walking pattern so as to avoid obstacle and walk smoothly. We generate via points of leg with respect to body motion, and then we use the genetic-fuzzy algorithm to search for the optimal via velocity and acceleration information of legs. All these methods are verified with PC simulation program, and implemented to SERO-V robot.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2003.09a
• /
• pp.228-231
• /
• 2003

This paper presents the leg trajectory generation for the quadruped robot with genetic-fuzzy algorithm. To have the nobility even at uneven terrain, a robot is able to recognize obstacles, and generates moving path of body that can avoid obstacles. This robot should have its own avoidance algorithm against obstacles, forwarding to target without collision. During walking period, n robot recognizes obstacle from external environment with a PSD and some interface, and this obstacle information is converted into proper the body rotation angle by fuzzy inference engine. After this process, we can infer the walking direction and walking distance of body, and finally can generate the optimal Beg trajectory using genetic algorithm. All these methods are verified with PC simulation program, and implemented to SERO-V robot.

• Proceedings of the KIEE Conference
• /
• 2006.10c
• /
• pp.202-204
• /
• 2006

In this paper, the detection scheme of the spatial coordinates based on stereo camera for a Transformation algorithm of an Leg-wheel Hexapod Robot is proposed. Robot designed as can have advantages that do transfer possibility fast mobility in flat topography and uneven topography through walk that use wheel drive. In the proposed system, using the disparity data obtained from the left and right images captured by the stereo camera system and the perspective transformation between a 3-D scene and an image plane, depth information can be detected. Robot uses construed environmental data and transformation algorithm, decide wheel drive and leg waik, and can calculate width of street and regulate width of robot.

• Proceedings of the KIEE Conference
• /
• 2005.05a
• /
• pp.252-254
• /
• 2005

Completer coverage path planning requires the robot path to cover every part of the workspace, which is an essential issue in cleaning robots and many other robotic applications such as vacuum robots and painter robots. In this paper, a novel Water Flowing Algorithm (WFA) is proposed for cleaning robots to complete coverage path planning in unknown environment without obstacles. The robot covers the whole workspace just like that water fills up a container. First the robot goes to the lowest point in the workspace just like water flows to the bottom of the container. At last the robot will come to highest point in the workspace just like water overflows from the container and simultaneously the robot has covered the whole workspace. The computer simulation results show that the proposed algorithm enable the robot to plan complete coverage paths.