• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2004.05a
• /
• pp.277-277
• /
• 2004

로봇의 실시간 장애물 회피 방법은 연구되어 왔고 실행되어 왔다. 이러한 방법을 vector field histogram(VFH)라 하며 이러한 방법은 알려져 있지 않는 장애물의 발견과 장애물과의 충돌을 피하는 동시에 목표점으로의 로봇의 이동을 위한 알고리즘이다. The vector field histogram(VFH)방법은 world model로 이차원 Cartesian histogram grid를 이용하였다. VFH 방법은 Vehicle을 원하는 데로 컨트롤하기 위한 과정으로 두 단계 데이터 줄이는 과정이다. Histogram grid 의 첫 번째 단계는 로봇의 순간위치를 구성하기 위한 일 차원 polar histogram에 포함된 각 섹터의 값은 polar obstacle density(POD)로 방향을 표시한다.(중략)

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.32 no.7
• /
• pp.69-75
• /
• 2004

An avoidance/guidance problem of an aircraft against moving obstacle is considered in two dimensional space. The aircraft is modelled as a point mass flying with constant speed. The lateral acceleration is assumed the control input. Artificial potential functions are applied to the terminal point and moving obstacles in order that repulsive forces and an attractive force are produced by the obstacles and the terminal point respectively. A real time guidance/avoidance law is proposed by using the potential forces and relative velocity. The guidance law for a logarithm potential function results the well-known proportional navigation law. The avoidance control command is inverse proportional to the time-to-go to the obstacle and turns the aircraft toward the negative direction of the line-of-sight change. The performance of the proposed guidance/avoidance law is verified with simulations.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.37 no.11
• /
• pp.1104-1111
• /
• 2009

In the low altitude, mission of the aircraft is restricted by a variety of threats such as anti-air missiles and terrain obstacles. Especially, aircraft have always a risk of ground collision near terrain. In this study, to effectively solve this problem, we developed the flight path generation algorithm that is considered the terrain avoidance. In this flight path generation algorithm, waypoints that should be passed by the UAV are selected first. The waypoints are located in the middle of the terrain obstacles. Then, physically meaningful waypoints sets are classified by Dijkstra algorithm. The optimal waypoint guidance law based on the optimal control theory is applied to produce trajectory candidates. And finally the minimum control energy trajectory is determined.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2003.06a
• /
• pp.321-324
• /
• 2003

There are two steps to solve the self-collision avoidance problems for redundant manipulators. First, all links are regarded as cylinders. and then the collisions should be checked among all pairs of the links. Between two cylinders. we can get the collision information derived from the concept or configuration space obstacle in real time. Therefore. it is possible to detect the links where collisions are likely in real time by setting the risk radius which is larger than actual radius. Second. the configuration control points (CCP) should be placed at the ends of the detected links. A cost function is the sum of the distances between the CCPs. To maximize the cost function means the links go far away each other without self-collisions.

• Journal of Advanced Navigation Technology
• /
• v.13 no.5
• /
• pp.646-655
• /
• 2009

This paper presents a new search strategy based on models of evolution in order to solve the problem of collision-free robotic path planning. We designed the robot path planning method with genetic algorithm which has become a well-known technique for optimization, intelligent search. Considering the path points as genes in a chromosome will provide a number of possible solutions on a given map. In this case, path distances that each chromosome creates can be regarded as a fitness measure for the corresponding chromosome. The effectiveness of the proposed genetic algorithm in the path planning was demonstrated by simulation. The proposed search strategy is able to use multiple and static obstacles.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.49 no.12
• /
• pp.981-988
• /
• 2021

This paper presents a decentralized guidance algorithm for swarm flight of fixed-wing UAVs (Unmanned Aerial Vehicles). Considering swarm flight missions, we assume four representative swarm tasks: gathering, loitering, waypoint/path following, and individual task. Those tasks require several distinct maneuvers such as path following, flocking, and collision avoidance. In order to deal with the required maneuvers, this paper proposes an integrated guidance algorithm based on vector field, augmented Cucker-Smale model, and potential field methods. Integrated guidance command is synthesized with heuristic weights designed for each guidance method. The proposed algorithm is verified through flight tests using up to 19 small fixed-wing UAVs.

• 전자공학회논문지 IE
• /
• v.47 no.2
• /
• pp.66-72
• /
• 2010

In an autonomous multi-mobile robot environment, optimal path planning without collision which connects the beginning and ending point is essential and primary important. Many mobile robots should move autonomously without prior or given information about obstacles which are stationary or dynamic. Collision free optimal path planning for multi mobile robots is proposed in this paper. The proposed approach is based on a potential field method and fuzzy logic system. First, a global path planner using potential field method selects the shortest path from each robot to its own target. Then, a local path planner modifies the path and orientation from the global planner to avoid collisions with static and dynamic obstacles using a fuzzy logic system. To verify performance of this method, several simulation-based experimental are done and their results are discussed. These results show that the path planning and collision avoidance strategies are effective and useful for multi-mobile robot systems.

• Spatial Information Research
• /
• v.22 no.1
• /
• pp.75-84
• /
• 2014

Power lines are one of the main obstacles causing an aircraft crash and thus their realtime detection is significantly important during flight. To avoid such flight obstacles, the use of LIDAR has been recently increasing thanks to its advantages that it is less sensitive to weather conditions and can operate in day and night. In this study, we suggest a fast method to detect power lines from LIDAR data for flight obstacle avoidance. The proposed method first extracts non-ground points by eliminating the points reflected from ground surfaces using a filtering process. Second, we calculate the eigenvalues for the covariance matrix from the coordinates of the generated non-ground points and obtain the ratio of eigenvalues. Based on the ratio of eigenvalues, we can classify the points on a linear structure. Finally, among them, we select the points forming horizontally long straight as power-line points. To verify the algorithm, we used both real and simulated data as the input data. From the experimental results, it is shown that the average detection rate and time are 80% and 0.2 second, respectively. If we would improve the method based on the experiment results from the various flight scenario, it will be effectively utilized for a flight obstacle avoidance system.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.24 no.4
• /
• pp.392-397
• /
• 2014

Recently, there are many researches on active safety system of intelligent vehicle. To reduce the probability of collision caused by driver's inattention and mistakes, the active safety system gives warning or controls the vehicle toward avoiding collision. For the purpose, it is necessary to recognize and analyze circumstances around. In this paper, we will treat the problem about collision risk assessment. In general, it is difficult to calculate the collision risk before it happens. To consider the uncertainty of the situation, Monte Carlo simulation can be employed. However it takes long computation time and is not suitable for practice. In this paper, we apply neural networks to solve this problem. It efficiently computes the unseen data by training the results of Monte Carlo simulation. Furthermore, we propose the features affects the performance of the assessment. The proposed algorithm is verified by applications in various crash scenarios.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.1128-1131
• /
• 1996

The collision-free path planning presented here uses linear parametric curve with one intermediate connection point between start and target points. The algorithm, in which connection point is organized in elliptic chord.(.theta., .delta.), maps objects in Euclidean Space into images in CPS through intersection check between path and obstacles a process defined as GM. Elliptic locus has special property that the total distance between focus points through a point on ellipse is the same regardless of .theta.. Hence by locating the start and target points to focus points of ellipse, and organizing connection point in elliptic coordinate, the .delta.-axis of CPS represents length of path. The GM of EWS requires calculation of interference in circumferential direction only. The procedures for GM is developed which include categorization of obstacles to reduce calculation amount. Simulations of GM of EWS, on a PC with Pentium/90MHz, is carried out to measure performance of algorithm and the results are reported on a table. The simulations are done for number of cases with different number of obstacles and location of start/target points.