• 한국산업융합학회 논문집
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• 제19권2호
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• pp.75-80
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• 2016

This study proposes a efficient technology to control the optimal trajectory planning and real-time implementation method which can perform autonomous travelling for unmaned factory automation. Online path planning should plan and execute alternately in a short time, and hence it enables the robot avoid unknown dynamic obstacles which suddenly appear on robot's path. Based on Route planning and control algorithm, we suggested representation of edge cost, heuristic function, and priority queue management, to make a modified Route planning algorithm. Performance of the proposed algorithm is verified by simulation test.

• 로봇학회논문지
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• 제18권3호
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• pp.251-259
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• 2023

In the path traveling of differential-drive robots, the steering controller plays an important role in determining the path-following performance. When a robot with a pure-pursuit algorithm is used to continuously drive a right-angled driving path in an unstructured environment without turning in place, the robot cannot accurately follow the right-angled path and stops driving due to the ground and motor load caused by turning. In the case of pure-pursuit, only the current robot position and the steering angle to the current target path point are generated, and the steering component does not reflect the speed plan, which requires improvement for precise path following. In this study, we propose a driving algorithm for differentially driven robots that enables precise path following by planning the driving speed using the radius of curvature and fusing the planned speed with the steering angle of the existing pure-pursuit controller, similar to the Model Predict Control control that reflects speed planning. When speed planning is applied, the robot slows down before entering a right-angle path and returns to the input speed when leaving the right-angle path. The pure-pursuit controller then fuses the steering angle calculated at each path point with the accelerated and decelerated velocity to achieve more precise following of the orthogonal path.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1048-1053
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• 2005

This paper presents design and integration of the ROBHAZ-DT3, which is a newly developed mobile robot system with chained double-track mechanisms. A passive adaptation mechanism equipped between the front and rear body enables the ROBHAZ-DT3 to have good adaptability to uneven terrains including stairs. The passive adaptation mechanism reduces energy consumption when moving on uneven terrain as well as its simplicity in design and remote control, since no actuator is necessary for adaptation. Based on this novel mobile platform, a rescue version of the ROBHAZ-DT3 with appropriate sensors and a semi-autonomous mapping and localization algorithm is developed to participate in the RoboCup2004 US-Open: Urban Search and Rescue Competition. From the various experiments in the realistic rescue arena, we can verify that the ROBHAZ-DT3 is reliable in traveling rugged terrain and the proposed mapping and localization algorithm are effective in the unstructured environment with uneven ground. The another application is an military robot for an EOD(Explosive Ordnance Disposal) and reconnaissance mission. The military version of the ROBHAZ-DT3 with a water disrupter, a thermal scope and a long distance wireless communication device is developed and sent to the area of military tactics in Iraq. Consequently, the feasibility of the military version of ROBHAZ-DT3 is verified.

• 한국지능시스템학회논문지
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• 제21권2호
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• pp.268-275
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• 2011

본 논문에서는 uDEAS(Univariate Dynamic Encoding Algorithm for Searches)를 이용하여 두 가지의 이동 로봇 최적 전역 경로 계획을 제안한다. 이동 로봇의 자율 주행을 위해서는 빠른 시간 내에 작업 공간에서의 최적 경로를 생성해야 한다. 따라서 본 논문에서는 이동 로봇의 실시간 최적 경로 계획을 위해 전역 경로 계획을 도입하여 장애물 지역과 비장애물 지역을 확인하고, 지도상의 노드점과 노트점을 이용하여 출발 지점과 도착 지점 사이의 기본 경로를 생성한다. 그리고 기본 경로를 사용하여 두 가지의 방법으로 경로를 생성하게 된다. 첫 번째 방법은 기본 경로에서 세 개의 노드점을 이용하여 대각선 경로를 생성하는 방법이다. 두 번째는 혼합 다항식의 파라미터를 uDEAS를 이용하여 탐색하고, 곡선 궤적을 생성하는 방법이다. 시뮬레이션을 통해 두개의 방법에 대해 비교 분석하였다.

• 한국정밀공학회지
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• 제26권6호
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• pp.74-80
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• 2009

Path tracking of unmanned vehicle is a basis of autonomous driving and navigation. For the path tracking, it is very important to find the exact position of a vehicle. GPS is used to get the position of vehicle and a direction sensor and a velocity sensor is used to compensate the position error of GPS. To detect path lines in a road image, the bird's eye view transform is employed, which makes it easy to design a lateral control algorithm simply than from the perspective view of image. Because the driving speed of vehicle should be decreased at a curved lane and crossroads, so we suggest the speed control algorithm used GPS and image data. The control algorithm is simulated and experimented from the basis of expert driver's knowledge data. In the experiments, the results show that bird's eye view transform are good for the steering control and a speed control algorithm also shows a stability in real driving.

• 한국산업융합학회 논문집
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• 제19권3호
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• pp.133-143
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• 2016

The objective in here is to find the density, stiffness, and strength of truss-wall rectangular (TWR) model which is combined with lattice truss (MLT) inside space. The TWR unit-cell model is defined as a unit cell originated from a solid-wall rectangular (SWR) model and it has an empty space inside. Thus, the empty space inside of the TWR is filled with lattice truss model defined as TWR-MLT. The ideal solutions derived of TWR-MLT are based on TWR with MLT model and it has developed by Gibson-Ashby's theory. To validate the ideal solutions of the TWR-MLT, ABAQUS software is applied to predict the density, strength, and stiffness, and then each of them are compared with the Gibson-Ashby's ideal solution as a log-log scale. Applied material property is stainless steel 304 because of cost effectiveness and easy to get around. For the analysis, SWR and TWR-MLT models are 1mm, 2mm, and 3mm truss diameter separately within a fixed 20mm opening width. In conclusion, the relative Young's modulus and relative yield strength of the TWR-MLT unit model is reasonably matched to the ideal expectations of the Gibson-Ashby's theory. In nearby future, TWR-MLT model can be verified by advanced technologies such as 3D printing skills.t.