• 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.

• 한국해양공학회지
• /
• 제33권6호
• /
• pp.510-517
• /
• 2019

Efficient path planning is essential for unmanned surface vehicle (USV) navigation. The A^* algorithm is an effective algorithm for identifying a safe path with optimal distance cost. In this study, a modified version of the A^* algorithm is applied for planning the path of a USV in a static and dynamic obstacle environment. The current study adopts the A^* approach while maintaining a safe distance between the USV and obstacles. Two important parameters-path length and computational time-are considered at various start times. The results demonstrate that the modified approach is effective for obstacle avoidance by a USV that is compliant with the International Regulations for Preventing Collision at Sea (COLREGs).

• 제어로봇시스템학회논문지
• /
• 제14권7호
• /
• pp.635-641
• /
• 2008

In this paper, we used a laser range finder (LRF) to detect both the static and dynamic obstacles for the safe navigation of a mobile robot. LRF sensor measurements containing the information of obstacle's geometry are first processed to extract the characteristic points of the obstacle in the sensor field of view. Then the dynamic states of the characteristic points are approximated using kinematic model, which are tracked by associating the measurements with Probability Data Association Filter. Finally, the collision avoidance algorithm is developed by using fuzzy decision making algorithm depending on the states of the obstacles tracked by the proposed obstacle tracking algorithm. The performance of the proposed algorithm is evaluated through experiments with the experimental mobile robot.

• 대한임베디드공학회논문지
• /
• 제19권3호
• /
• pp.131-139
• /
• 2024

Crew Transfer Vessels (CTVs) are primarily used for the maintenance of offshore wind farms. Despite being manually operated by professional captains and crew, collisions with other ships and marine structures still occur. To prevent this, the introduction of autonomous navigation systems to CTVs is necessary. In this study, research on the obstacle avoidance system of the autonomous navigation system for CTVs was conducted. In particular, research on obstacle avoidance simulation for CTVs using deep reinforcement learning was carried out, taking into account the currents and wind loads in offshore wind farms. For this purpose, 3 degrees of freedom ship maneuvering modeling for CTVs considering the currents and wind loads in offshore wind farms was performed, and a simulation environment for offshore wind farms was implemented to train and test the deep reinforcement learning agent. Specifically, this study conducted research on obstacle avoidance maneuvers using MATD3 within deep reinforcement learning, and as a result, it was confirmed that the model, which underwent training over 10,000 episodes, could successfully avoid both static and moving obstacles. This confirms the conclusion that the application of the methods proposed in this study can successfully facilitate obstacle avoidance for autonomous navigation CTVs within offshore wind farms.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2000년도 하계종합학술대회 논문집(5)
• /
• pp.31-34
• /
• 2000

In this paper, we design an optimal path for multiple mobile robots. For this purpose, we propose a new method of path planning for multiple mobile robots in dynamic environment. First, every mobile robot searches a global path using a distance transform algorithm. Then we put subgoals at crooked path points and optimize them. And finally to obtain an optimal on-line local path, ever)r mobile robot searches a new path with static and dynamic obstacle avoidance.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2003년도 ICCAS
• /
• pp.645-650
• /
• 2003

Legged robots can avoid an obstacle by crawling-over or striding, according to the obstacle’s nature and the current state of the robot. Thus, it can be observed that the mobility efficiency to reach a destination is improved by such action. Moreover, if robots have many legs like 4-legged or 6-legged types, then the robot movement range is affected by the order of swing leg. In this paper, the avoidance action of a quadruped robot is generated by a neural network (NN) whose inputs are information on the position of the destination, the obstacle configuration and the robot's self-state. To realize a free gait in static walking, the order of swing leg is determined using an another NN whose inputs are the amount of movements and the robot’s self-state. The design parameter of the latter NN is adjusted by using genetic algorithm (GA).

• 한국생산제조학회지
• /
• 제19권1호
• /
• pp.145-155
• /
• 2010

This paper presents a new approach to obstacle avoidance for mobile robot in unknown or partially unknown environments. The method combines two navigation subsystems: low level and high level. The low level subsystem takes part in the control of linear, angular velocities using a multivariable PI controller, and the nonlinear position control. The high level subsystem uses ultrasonic and IR sensors to detect the unknown obstacle include static and dynamic obstacle. This approach provides both obstacle avoidance and target-following behaviors and uses only the local information for decision making for the next action. Also, we propose a new algorithm for the identification and solution of the local minima situation during the robot's traversal using the set of fuzzy rules. The system has been successfully demonstrated by simulations and experiments.

• Journal of Information Processing Systems
• /
• 제16권2호
• /
• pp.406-420
• /
• 2020

In order to make up the deficiencies of the existing research results which cannot effectively deal with the nearest neighbor query based on the line segments in obstacle space, the k nearest neighbor query method of line segment in obstacle space is proposed and the STA_OLkNN algorithm under the circumstance of static obstacle data set is put forward. The query process is divided into two stages, including the filtering process and refining process. In the filtration process, according to the properties of the line segment Voronoi diagram, the corresponding pruning rules are proposed and the filtering algorithm is presented. In the refining process, according to the relationship of the position between the line segments, the corresponding distance expression method is put forward and the final result is obtained by comparing the distance. Theoretical research and experimental results show that the proposed algorithm can effectively deal with the problem of k nearest neighbor query of the line segment in the obstacle environment.

• 한국지능시스템학회논문지
• /
• 제13권6호
• /
• pp.686-691
• /
• 2003

인간의 작업을 보조 혹은 대신하기 위해서 인간과 흡사한 이족보행로봇에 대한 연구가 많이 진행되고 있다. 이족보행로봇이 인간을 대신해서 작업을 하기 위해서는 작업공간에서의 자유로운 이동과 장애물 대처능력은 반드시 필요한 기능이다. 본 논문에서는 안정된 정적보행 및 장애물을 지능적으로 대처하는 이족보행로봇의 보행알고리즘을 제안하였다. 먼저 장애물 대처 가능한 이족보행로봇의 기구 설계 및 원격제어 가능한 제어시스템 구현에 대하여 설명하고, 인간의 보행분석 결과를 바탕으로 정적보행 알고리즘을 제안하였다. 또한 발에 부착된 적외선센서로 장애물을 인식하여 장애물의 형태에 따라 좌우 회전 및 옆 걸음을 통한 장애물 회피알고리즘, 거리보정 알고리즘을 사용한 장애물 넘어가기 알고리즘을 제안하였다. 제안한 보행알고리즘들은 이족보행로봇을 실제 제작하여 다양한 작업환경에서 실험으로 성능을 검증하였다.

• 한국콘텐츠학회논문지
• /
• 제19권3호
• /
• pp.72-79
• /
• 2019

자율 주행은 이동 로봇의 핵심적 기술로써, 측정된 센서 정보를 토대로 불확실한 위치 정보를 이용한 지도 작성 및 수정 기능과, 불확실한 지도 및 센서 정보를 이용한 로봇의 위치 인식 기능으로 구성된다. 자율주행은 이러한 주행 위치의 불확실성에 기반한 확률론적 방법론과 함께 주행 시 장애물의 감지 및 회피 경로의 생성, 반복적 주행 패턴에 따른 경로 관리 기능이 필수적 요소이다. 거리 기반의 스캐너를 통해 관측된 센서 입력은, 지도 구성에 사용된 벽과 같은 정적 물체와 주행 시의 사람처럼 움직이는 동적 물체와의 구별이 필요하기 ?문에 장애물 감지에 어려움이 있다. 본 논문에서는, 이러한 자율 주행 환경에서 기존의 정적, 동적 개체의 판별 방식과 비교하여, 장애물 회피를 위한 저해상도 격자 공간의 생성 및 강화학습을 이용한 경로 생성을 다루고자 한다. 최종적으로 실험을 통해 제안된 방법론의 실효성을 검증하고자 한다.