• Proceedings of the KIEE Conference
• /
• 2005.05a
• /
• pp.261-265
• /
• 2005

In this paper, we constructed the infrastructure with wireless LAN and Access Point in the indoor environment and implemented the teleoperation. Wireless LAN based teleoperation system is irregular communication delay according to environment condition and occurrence possibility of blackout is very high. In this paper, In case these problem happened, we measured communication delay time by real time, and did mobile robot to control harmoniously through vision and force reflection information. Also, we present obstacle-avoidance mode that mobile robot can travel without collision using direction information in case communication delay time is large. We proved usefulness of presented algorithm through teleoperation experiment to apply presented algorithm.

• Proceedings of the KIEE Conference
• /
• 2006.07d
• /
• pp.1983-1986
• /
• 2006

In this paper, we construct the infrastructure for the teleoperating system of mobile robots. For the stable teleoperating system, we develope an algorithm that measure communication time delay on real-time. We propose the force-reflected teleoperation method that control the stiffness of joystick according to VFH(Vector Field Histogram). Also, an obstacle avoidance method using VFH is presented for the mobile robot to move to the indicated direction without collision. Experiments are conducted to demonstrate the feasibility of the proposed methods.

• KIPS Transactions on Software and Data Engineering
• /
• v.8 no.6
• /
• pp.243-250
• /
• 2019

Because of a moving UAV has a lot of potential/kinetic energy, if the UAV falls to the ground, it may have a lot of impact. Because this can lead to human casualities, in this paper, the population density area on the UAV flight path is defined as a dangerous area. The conventional UAV path flight was a passive form in which a UAV moved in accordance with a path preset by a user before the flight. Some UAVs include safety features such as a obstacle avoidance system during flight. Still, it is difficult to respond to changes in the real-time flight environment. Using public Big Data for UAV path flight can improve response to real-time flight environment changes by enabling detection of dangerous areas and avoidance of the areas. Therefore, in this paper, we propose a method to detect and avoid dangerous areas for UAVs by utilizing the Big Data collected in real-time. If the routh is designated according to the destination by the proposed method, the dangerous area is determined in real-time and the flight is made to the optimal bypass path. In further research, we will study ways to increase the quality satisfaction of the images acquired by flying under the avoidance flight plan.

• Journal of IKEEE
• /
• v.25 no.2
• /
• pp.337-343
• /
• 2021

Deep reinforcement learning is an artificial intelligence algorithm that enables learners to select optimal behavior based on raw and, high-dimensional input data. A lot of research using this is being conducted to create an optimal movement path of a mobile robot in an environment in which obstacles exist. In this paper, we selected the Dueling Double DQN (D3QN) algorithm that uses the prioritized experience replay to create the moving path of mobile robot from the image of the complex surrounding environment. The virtual environment is implemented using Webots, a robot simulator, and through simulation, it is confirmed that the mobile robot grasped the position of the obstacle in real time and avoided it to reach the destination.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.17 no.7
• /
• pp.901-906
• /
• 2007

Algorithms of path planning and obstacle avoidance are essential to autonomous mobile robots that are working in unknown environments in the real time. This paper presents a new navigation algorithm for an autonomous mobile robot with vision and IR sensors using fuzzy rules. Temporary targets are set up by distance variation method and then the algorithms of trajectory planning and obstacle avoidance are designed using fuzzy rules. In this approach, several digital image processing technique is employed to detect edge of obstacles and the distances between the mobile robot and the obstacles are measured. An autonomous mobile robot with single vision and IR sensors is built up for experiments. We also show that the autonomous mobile robot with the proposed algorithm is navigating very well in complex unknown environments.

• Journal of Institute of Control, Robotics and Systems
• /
• v.15 no.9
• /
• pp.946-951
• /
• 2009

The small multi-jointed robots for most education are developed with the way of firmware. But the firmware may be very difficult to develop as gradually increasing throughputs and control routines. Due to limit of firmware we try to use on RTOS, but hard to adapt on the small multi-jointed robots. It would be hard to install RTOS into the small multi-jointed robots because of the size capacity of RTOS, and lack of libraries for control of the particular hardware. Moreover, even its RTOS with many functions causes its to make overheads scheduling, TCB (Task Control Block), and task states. Also to keep maintenance of RTOS, it is composed of components for the whole structure of my proposed RTOS. Additionally, We provided with libraries of servo motor and sensor control and developed RMS (Rate Montonic scheduler) to handle tasks on real time and reduce overheads. Therefore, It is possible to work the fixed priority and task preemptive way. We show one example of the multi-jointed robot installed with my proposed RTOS, which shows to obstacle avoidance and climbing up the slope.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.34S no.12
• /
• pp.19-29
• /
• 1997

This paper presents stable kinematic modeling and path planning and path tracking algorithms for the poisition control of 4-wheeled 2-d.o.f(degree of freedom) mobile robot. We drived the actuated inverse and sensed forward solution for the calculation of actuator velocity and robot velocities. the deal-reckoning algorithm is introduced to calculate the position of WMR in real time. The gaussian functions are applied to control and to design the smooth orientation angle of WMR and the path planning algorithm for obstacle avoidance is prosed. We composed feedback control system to compensate for error because of uncertainty kinematic modeling and measurement noise. The simulation resutls show that the proposed kinematkc modeling and path planning and feedback control algorithms are useful.

• Journal of Institute of Control, Robotics and Systems
• /
• v.5 no.2
• /
• pp.180-188
• /
• 1999

The objective of this paper is, based upon the principles of artificial life, to induce emergent behaviors of multiple autonomous mobile robots which complex global intelligence form from simple local interactions. Here, we propose an architecture of neural network learning with reinforcement signals which perceives the neighborhood information and decides the direction and the velocity of movement as mobile robots navigate in a group. As the results of the simulations, the optimum weight is obtained in real time, which not only prevent the collisions between agents and obstacles in the dynamic environment, but also have the mobile robots move and keep in various patterns.

• Proceedings of the KIEE Conference
• /
• 1998.07g
• /
• pp.2189-2192
• /
• 1998

The objective of this paper is, based upon the principles of artificial life, to induce emergent behaviors of multiple autonomous mobile robots which form from simple local rules to complex global intelligence. Here, we propose an architecture of neural network learing with reinforcement signals which perceives the neighborhood information and decides the direction and the velocity of movement as mobile robots navigates in a group. As results of the simulations, the optimum weights are obtained in real time, which not only prevent from the collisions between agents and obstacles in the dynamic environment, but also have the mobile robots move and keep in various patterns.

• Advances in robotics research
• /
• v.1 no.1
• /
• pp.21-39
• /
• 2014

Due to the rapid progress in the field of robotics, it is a high time to concentrate on the development of a robot that can manoeuvre in all type of landscapes, ascend and descend stairs and sloping surfaces autonomously. This paper presents details of a prototype robot which can navigate in very rough terrain, ascend and descend staircase as well as sloping surface and cross ditches. The robot is made up of six differentially steered wheels and some passive mechanism, making it suitable to cross long ditches and landscape undulation. Static stability of the developed robot have been carried out analytically and navigation capability of the robot is observed through simulation in different environment, separately. Description of embedded system of the robot has also been presented and experimental validation has been made along with some details on obstacle avoidance. Finally the limitations of the robot have been explored with their possible reasons.