• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제9권4호
• /
• pp.315-320
• /
• 2009

The popularity of autonomous mobile robots have been rapidly increasing due to their new emerging application areas, from room cleaning, tourist guidance to space explorations. However, the development of a satisfactory control algorithm that will enable the autonomous mobile robots to navigate safely especially in dynamic environments is still an open research problem. In this paper, a newly proposed potential field based control method is implemented, analyzed, and improvements are suggested based on experimental results obtained from simulations. The experimental results are presented to show the effectiveness of the behavior-based control using the proposed potential field generation technique.

• 한국지능시스템학회논문지
• /
• 제22권4호
• /
• pp.476-480
• /
• 2012

본 논문에서는 선도 로봇을 추종하는 군집 로봇의 대형 제어를 인공 포텐셜 장을 사용하여 제안한다. 또한, 인공 포텐셜 장은 물리적으로 해석하기 쉬운 전기장을 모델링하여 구성하고, 장애물을 더욱 효과적으로 모델링하기 위해서, 장애물의 모양에 따라 전기장의식을 달리한다. 제안하는 방법은 선도 로봇의 경로를 인공 포텐셜 장을 통해 계획한 뒤, 선도 로봇을 추종 로봇이 뒤따라가는 형태로 구성된다. 마지막으로 시뮬레이션 예제를 통해 제안하는 기법의 타당성을 검증한다.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1999년도 하계학술대회 논문집 G
• /
• pp.3004-3006
• /
• 1999

In this paper, we present the ball position and path plain method for the robot-soccer using optical flow. As we compare a optical flow method with a general method within the accurate and effective ball position information of robot-soccer or the path planning, we prove accurate and effective optical flow algorithm to apply ball position and path plain for robot-soccer

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2004년도 ICCAS
• /
• pp.1544-1549
• /
• 2004

A new collision avoidance algorithm is presented for two mobile robots in narrow corridor environments. When two robots meet each other in a narrow corridor, one should yield the way to the other robot. To solve the problem arising in this situation, they exchange their path to get information about crossing-points to check avoidance conditions, which are necessary for choosing the robot to yield. The conditions are summarized as follows. 1) If one robot blocks the path to the closest crossing-point in front of the other robot. 2) If the closest crossing-point of each robot is the same point. 3) Which robot is closer to the closest crossing-point. In this paper, we propose a path planning algorithm for the robot which yield the way. Simulation results are presented to verify the feasibility of the proposed collision avoidance algorithm.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
• /
• pp.1140-1143
• /
• 1996

A new approach based on artificial potential function is proposed for the obstacle avoidance of redundant manipulators. Unlike the so-called "global" path planning method, which requires expensive computation for the path search before the manipulator starts to move, this new approach, "local" path planning, researches the path in real-time using the local distance information. Previous use of artificial potential function has exhibited local minima in some complex environments. This thesis proposes a potential function that has no local minima even for a cluttered environment. This potential function has been implemented for the collision avoidance of a redundant robot in Simulation. The simulation also employ an algorithm that eliminates collisions with obstacles by calculating the repulsive potential exerted on links, based on the shortest distance to object.

• 한국정밀공학회지
• /
• 제29권12호
• /
• pp.1321-1330
• /
• 2012

This paper describes an advanced formation algorithm of clustered multiple robots for their navigation using flexible formation method for collision avoidance under static environment like narrow corridors. A group of clustered multiple robots finds the lowest path cost for navigation by changing its formation. The suggested flexible method of formation transforms the basic group of mobile robots into specific form when it is confronted by particular geographic feature. In addition, the proposed method suggests to choose a leader robot of the group for the obstacle avoidance and path planning. Firstly, the group of robots forms basic shapes such as triangle, square, pentagon and etc. depending on number of robots. Secondly, the closest to the target location robot is chosen as a leader robot. The chosen leader robot uses $A^*$ for reaching the goal location. The proposed approach improves autonomous formation characteristics and performance of all system.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
• /
• pp.601-606
• /
• 1998

In this paper, we propose a new design method of an optimal fuzzy logic controller using co-evolutionary concept. In general, it is very difficult to find optimal fuzzy rules by experience when the input and/or output variables are going to increase. Futhermore proper fuzzy partitioning is not deterministic ad there is no unique solution. So we propose a co-evolutionary method finding optimal fuzzy rules and proper fuzzy membership functions at the same time. Predator-Prey co-evolution and symbiotic co-evolution algorithms, typical approaching methods to co-evolution, are reviewed, and dynamic fitness landscape associated with co-evolution is explained. Our algorithm is that after constructing two population groups made up of rule base and membership function, by co-evolving these two populations, we find optimal fuzzy logic controller. By applying the propose method to a path planning problem of autonomous mobile robots when moving objects applying the proposed method to a pa h planning problem of autonomous mobile robots when moving objects exist, we show the validity of the proposed method.

• 자동차안전학회지
• /
• 제11권3호
• /
• pp.30-36
• /
• 2019

This paper suggests a car-following algorithm for urban environment, with multiple target candidates. Until now, advanced driver assistant systems (ADASs) and self-driving technologies have been researched to cope with diverse possible scenarios. Among them, car-following driving has been formed the groundwork of autonomous vehicle for its integrity and flexibility to other modes such as smart cruise system (SCC) and platooning. Although the field has a rich history, most researches has been focused on the shape of target trajectory, such as the order of interpolated polynomial, in simple single-lane situation. However, to introduce the car-following mode in urban environment, realistic situation should be reflected: multi-lane road, target's unstable driving tendency, obstacles. Therefore, the suggested car-following system includes both in-lane preceding vehicle and other factors such as side-lane targets. The algorithm is comprised of three parts: path candidate generation and optimal trajectory selection. In the first part, initial guesses of desired paths are calculated as polynomial function connecting host vehicle's state and vicinal vehicle's predicted future states. In the second part, final target trajectory is selected using quadratic cost function reflecting safeness, control input efficiency, and initial objective such as velocity. Finally, adjusted path and control input are calculated using model predictive control (MPC). The suggested algorithm's performance is verified using off-line simulation using Matlab; the results shows reasonable car-following motion planning.

• 한국항행학회논문지
• /
• 제27권4호
• /
• pp.365-373
• /
• 2023

무인 항공기는 다양한 분야에서 널리 활용되고 있으며, 실시간 경로 재계획은 이들 기기의 안전성과 효율성을 향상하는 핵심 요소이다. 본 논문에서는 RRT*와 LOSPO를 기반으로 한 실시간 경로 재계획 기법을 제안한다. 제안된 기법은 먼저 RRT* 알고리즘을 활용하여 초기 경로를 생성하고, LOSPO를 이용하여 경로를 최적화한다. 또한 최적화된 경로를 궤적으로 변경하여 실제 시간과 항공기의 동적한계를 고려할 수 있다. 이 과정에서 환경 변화와 충돌 위험을 실시간으로 감지하고, 필요한 경우 경로를 재계획함으로써 안전한 운행을 유지한다. 이 방법은 시뮬레이션을 통한 실험을 통해 검증되었다. 본 논문의 결과는 무인 항공기의 실시간 경로 재계획에 관한 연구에 중요한 기여할 것으로 기대한다. 또한 이 기법을 다양한 상황에 적용함으로써 무인 항공기의 안전성과 효율성을 향상시킬 수 있다.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2005년도 ICCAS
• /
• pp.2237-2242
• /
• 2005

The original RRT is iteratively expanded by applying control inputs that drive the system slightly toward randomly-selected states, as opposed to requiring point-to-point convergence, as in the probabilistic roadmap approach. It is generally known that the performance of RRTs can be improved depending on the selection of the metrics in choosing the nearest vertex and bias techniques in choosing random states. We designed a path planning algorithm based on the RRT method for a remote-controlled mobile robot. First, we considered a bias technique that is goal-biased Gaussian random distribution along the command directions. Secondly, we selected the metric based on a weighted Euclidean distance of random states and a weighted distance from the goal region. It can save the effort to explore the unnecessary regions and help the mobile robot to find a feasible trajectory as fast as possible. Finally, the constraints of the actuator should be considered to apply the algorithm to physical mobile robots, so we select control inputs distributed with commanded inputs and constrained by the maximum rate of input change instead of random inputs. Simulation results demonstrate that the proposed algorithm is significantly more efficient for planning than a basic RRT planner. It reduces the computational time needed to find a feasible trajectory and can be practically implemented in a remote-controlled mobile robot.