• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2005년도 ICCAS
• /
• pp.1657-1661
• /
• 2005

The velocity dipole field method is presented for real-time collision avoidance of mobile robots. The direction of motion of the obstacle is used as the axis of the dipole field, and the speed of the obstacle is used to proportionally strengthen the dipole field. The elliptical field lines of the dipole field are useful to skillfully guide the robot around obstacles, quite similar to the way humans avoid moving obstacles. Field modulation coefficient is also introduced to weaken the field effect as the obstacle recedes. The real-time algorithm of the velocity dipole field has been devised and experimentally tested on the robot soccer test-bed. The results show the capability of the new real-time collision avoidance strategy and how it can overcome the weaknesses in the conventional potential field method. The new method makes an explicit and proactive action of collision avoidance, unlike the conventional method, which forces the robot merely away from the obstacle aimlessly. The proposed method delivers greater capability with no considerable computational overhead

• 한국산업융합학회 논문집
• /
• 제22권2호
• /
• pp.209-218
• /
• 2019

This study proposes a new approach to Control the Orientation and position based on obstacle avoidance technology by multi sensors fusion and autonomous travelling control of mobile robot system for implimentation of Smart FA. The important focus is to control mobile robot based on by the multiple sensor module for autonomous travelling and obstacle avoidance of proposed mobile robot system, and the multiple sensor module is consit with sonar sensors, psd sensors, color recognition sensors, and position recognition sensors. Especially, it is proposed two points for the real time implementation of autonomous travelling control of mobile robot in limited manufacturing environments. One is on the development of the travelling trajectory control algorithm which obtain accurate and fast in considering any constraints. such as uncertain nonlinear dynamic effects. The other is on the real time implementation of obstacle avoidance and autonomous travelling control of mobile robot based on multiple sensors. The reliability of this study has been illustrated by the computer simulation and experiments for autonomous travelling control and obstacle avoidance.

• 로봇학회논문지
• /
• 제3권3호
• /
• pp.212-218
• /
• 2008

Collision avoidance is a fundamental and important task of an autonomous mobile robot for safe navigation in real environments with high uncertainty. Obstacles are classified into static and dynamic obstacles. It is difficult to avoid dynamic obstacles because the positions of dynamic obstacles are likely to change at any time. This paper proposes a scheme for vision-based avoidance of dynamic obstacles. This approach extracts object candidates that can be considered moving objects based on the labeling algorithm using depth information. Then it detects moving objects among object candidates using motion vectors. In case the motion vectors are not extracted, it can still detect the moving objects stably through their color information. A robot avoids the dynamic obstacle using the dynamic window approach (DWA) with the object path estimated from the information of the detected obstacles. The DWA is a well known technique for reactive collision avoidance. This paper also proposes an algorithm which autonomously registers the obstacle color. Therefore, a robot can navigate more safely and efficiently with the proposed scheme.

• 한국항행학회논문지
• /
• 제22권6호
• /
• pp.623-629
• /
• 2018

본 논문에서는 무인항공기용 실시간 장애물 탐지 및 회피 경로 생성 알고리즘을 제안한다. 2-D Lidar를 이용하여 장애물을 검출하고, 검출 정보는 지역 회피 경로 생성을 위한 실시간 히스토그램 생성과 목표 지점까지 전역 회피 경로 생성을 위해 사용되는 2-D SLAM 지도를 생성하는데 사용된다. 지역 회피 경로 생성을 위한 VFH 알고리즘은 장애물들이 벡터 방향과 거리에 따라 얼마큼 분포되어 있는지에 대한 실시간 히스토그램을 생성하고, 이 히스토그램은 근접 장애물 검출 시 지역 회피 경로를 생성하는데 사용된다. 기존의 $RRT^*-Smart$ 알고리즘의 한계로 인해 Modified $RRT^*-Smart$ 알고리즘을 제안한다. 이 알고리즘은 새로운 노드가 생길 때 목표 지점과의 직선 경로 여부를 판단하고, 목표 지점 방향으로 생성되도록 방향성을 부여하며, 노드의 길이를 확률적으로 나누어 일정한 단위의 길이가 아닌 랜덤 단위의 길이로 퍼뜨림으로써 보다 적은 비용으로 목표 지점까지의 효율적인 전역 회피경로를 생성한다. 본 논문에서는 효율적인 회피경로를 생성하여 회피 기동함을 다양한 시뮬레이션 실험환경을 통해 검증하였다.

• 한국생산제조학회지
• /
• 제7권1호
• /
• pp.9-21
• /
• 1998

This paper a new solution approach to moving obstacle avoidance problem of a mobile robot. A new concept avoidability measure (AVM) is defined to describe the state of a pair of a robot and an obstacle regarding the collision between them. As an AVM, virtual distance function (VDF), is derived as a function of the distance from the obstacle to the robot and outward speed of the obstacle relative to the robot. By keeping the virtual distance above some positive limit value, the robot avoids the obstacle. In terms of the VDF ,an artificial potential field is constructed to repel the robot away from the obstacle and to attract the robot toward a goal location. At every sampling time, the artificial potential field is updated and the force driving the robot is derived from the gradient of the artificial potential field. The suggested algorithm drives the robot to avoid moving obstacles in real time. Since the algorithm considers the mobility of the obstacle as well as the distance, it is effective for moving obstacle avoidance. Some simulation studies show the effectiveness of the proposed approach.

• 로봇학회논문지
• /
• 제4권2호
• /
• pp.105-111
• /
• 2009

In this paper, we provide experimental results and verification for obstacle avoidance algorithm 'ELA(Emergency Level Around)', which is applicable to rescue robots. ELA is a low level intelligence-based obstacle avoidance algorithm, so can be used in fast mobile robots requiringhigh speed in operation with little computational load. Constructed system for experiments consist of laptop, sensors, peripheral devices and mobile robot platform VSTR(Variable Single-tracked Robot) to realize predetermined scenarios. Finally, experiment was conducted in indoor surroundings including miscellaneous things as well as dark environment to show fitness and robustness of ELA for rescue, and it is shown that VSTR navigates endowed area well with real-time obstacle avoidance based on ELA. Therefore, it is concluded that ELA can be a candidate algorithm to increase mobility of rescue robots in real situation.

• 로봇학회논문지
• /
• 제3권3호
• /
• pp.186-193
• /
• 2008

We propose a novel real-time obstacle avoidance method for rescue robots. This method, named the ELA(Emergency Level Around), permits the detection of unknown obstacles and avoids collisions while simultaneously steering the mobile robot toward safe position. In the ELA, we consider two sensor modules, PSD(Position Sensitive Detector) infrared sensors taking charge of obstacle detection in short distance and LMS(Laser Measurement System) in long distance respectively. Hence if a robot recognizes an obstacle ahead by PSD infrared sensors first, and judges impossibility to overcome the obstacle based on driving mode decision process, the order of priority is transferred to LMS which collects data of radial distance centered on the robot to avoid the confronted obstacle. After gathering radial information, the ELA algorithm estimates emergency level around a robot and generates a polar histogram based on the emergency level to judge where the optimal free space is. Finally, steering angle is determined to guarantee rotation to randomly direction as well as robot width for safe avoidance. Simulation results from wandering in closed local area which includes various obstacles and different conditions demonstrate the power of the ELA.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
• /
• pp.434-439
• /
• 1993

This paper present a sensor based obstacle avoidance method which is based on a VFH(Vector Field Histogram) method. The basic idea of obstacle avoidance is to find a minimum obstacle direction and distance. From the minimum sonar index and the target direction high level system determine steering angle of mobile robot. The sonar sensor system consists of 12 ultra sonic sensor, and each sensor have its direction and safety value. This method has advantage on calculation speed and small memory. This method is implemented on indoor autonomous vehicle'ALiVE-2'.

• 한국공작기계학회:학술대회논문집
• /
• 한국공작기계학회 1998년도 춘계학술대회 논문집
• /
• pp.88-93
• /
• 1998

This paper presents a new solution approach to moving obstacle avoidance problem for a mobile robot. A new concept avoidability measure(AVM) is defined to describe the state of a pair of a robot and an obstacle regarding the collision between them. As an AVM, virtual distance function(VDF) is derived as a function of the distance from the obstacle to the robot and outward speed of the obstacle relative to the robot. By keeping the virtual distance above some positive limit value, the robot avoids the obstacle. In terns of the VDF, an artificial potential field is constructed to repel the robot away from the obstacle and to attract the robot toward a goal location. At every sampling time, the artificial potential field is updated and the force driving the robot is derived form the gradient of the artificial potential field. The suggested algorithm drives the robot to avoid moving obstacles in real time. Since the algorithm considers the mobility of the obstacle as well as the distance, it is effective for moving obstacle avoidance. Some simulation studies show the effectiveness of the proposed approach.

• 제어로봇시스템학회논문지
• /
• 제5권3호
• /
• pp.338-343
• /
• 1999

In this paper, the fuzzy neural network for the obstacle avoidance, which consists of the straight-line navigation and the barrier elusion navigation, is proposed and examined. For the straight-line navigation, the fuzzy neural network gets two inputs, angle and distance between the line and the mobile robot, and produces one output, steering velocity of the mobile robot. For the barrier elusion navigation, four ultrasonic sensors measure the distance between the barrier and the mobile robot and provide the distance information to the network. Then the network outputs the steering velocity to navigate along the obstacle boundary. Training of the proposed fuzzy neural network is executed in a given environment in real-time. The weights adjusting uses the back-propagation of the gradient of error to be minimized. Computer simulations are carried out to examine the efficiency of the real time learning and the guiding ability of the proposed fuzzy neural network. It has been shown that the mobile robot that employs the proposed fuzzy neural network navigates more safely with and less trembling locus compared with the previous reported efforts.