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Study on Path Planning Algorithms for Unmanned Agricultural Helicopters in Complex Environment
Sang-Woo Moon,David Hyun-Chul Shim 한국항공우주학회 2009 International Journal of Aeronautical and Space Sc Vol.10 No.2
In this paper, two algorithms to solve the path planning problem with constraints from obstacles are presented. One proposed Algorithm is “Grid point-based path planning”. The first step of this algorithm is to set points which can be the waypoints around the field. These points can be located inside or outside of the field or the obstacles. Therefore, we should determine whether those points are located in the field or not. Using the equations of boundary lines for a region that we are interested in is an effective approach to handle. The other algorithm is based on the boundary lines of the agricultural field, and the concept of this algorithm is well known as “boustrophedon method”. These proposed algorithms are simple but powerful for complex cases since it can generate a plausible path for the complex shape which cannot be represented by using geometrical approaches efficiently and for the case that some obstacles or forbidden regions are located on the field by using a skill of discriminants about set points. As will be presented, this proposed algorithm could exhibit a reasonable accuracy to perform an agricultural mission.
Study on Path Planning Algorithms for Unmanned Agricultural Helicopters in Complex Environment
Moon, Sang-Woo,Shim, David Hyun-Chul The Korean Society for Aeronautical and Space Scie 2009 International Journal of Aeronautical and Space Sc Vol.10 No.2
In this paper, two algorithms to solve the path planning problem with constraints from obstacles are presented. One proposed Algorithm is "Grid point-based path planning". The first step of this algorithm is to set points which can be the waypoints around the field. These points can be located inside or outside of the field or the obstacles. Therefore, we should determine whether those points are located in the field or not. Using the equations of boundary lines for a region that we are interested in is an effective approach to handle. The other algorithm is based on the boundary lines of the agricultural field, and the concept of this algorithm is well known as "boustrophedon method". These proposed algorithms are simple but powerful for complex cases since it can generate a plausible path for the complex shape which cannot be represented by using geometrical approaches efficiently and for the case that some obstacles or forbidden regions are located on the field by using a skill of discriminants about set points. As will be presented, this proposed algorithm could exhibit a reasonable accuracy to perform an agricultural mission.
Guidance Law for Vision-Based Automatic Landing of UAV
Min, Byoung-Mun,Tahk, Min-Jea,Shim, Hyun-Chul David,Bang, Hyo-Choong The Korean Society for Aeronautical and Space Scie 2007 International Journal of Aeronautical and Space Sc Vol.8 No.1
In this paper, a guidance law for vision-based automatic landing of unmanned aerial vehicles (UAVs) is proposed. Automatic landing is a challenging but crucial capability for UAVs to achieve a fully autonomous flight. In an autonomous landing maneuver of UAVs, the decision of where to landing and the generation of guidance command to achieve a successful landing are very significant problem. This paper is focused on the design of guidance law applicable to automatic landing problem of fixed-wing UAV and rotary-wing UAV, simultaneously. The proposed guidance law generates acceleration command as a control input which derived from a specified time-to-go ($t_go$) polynomial function. The coefficient of $t_go$-polynomial function are determined to satisfy some terminal constraints. Nonlinear simulation results using a fixed-wing and rotary-wing UAV models are presented.
End to End 학습 기반 자율 주행 프레임워크 개발 및 실차 기반 실험
정찬영(Chan-Young Jung),성현기(Hyun-Ki Seong),심현철(David Hyun-Chul Shim) 제어로봇시스템학회 2020 제어·로봇·시스템학회 논문지 Vol.26 No.5
In recent years, autonomous vehicles have been developed by various approaches for traffic safety and driver convenience. End-to-end learning-based autonomous driving has gained enormous attention in conjunction with deep learning technologies in which perception, planning, and control of the conventional autonomous driving algorithm are trained by a single deep neural network. In this paper, we present the end-to-end learning-based autonomous driving framework. The framework consisted of three parts: data acquisition in real-world and simulated environments, network design and optimization, and performance evaluation. Our framework was integrated on a full-scale autonomous vehicle platform and evaluated with various performance metrics.
Oh, Hyon-Dong,Won, Dae-Yeon,Huh, Sung-Sik,Shim, David Hyun-Chul,Tahk, Min-Jea The Korean Society for Aeronautical and Space Scie 2010 International Journal of Aeronautical and Space Sc Vol.11 No.2
This paper describes the experimental framework for the control system design and validation of a rotorcraft unmanned aerial vehicle (UAV). Our approach follows the general procedure of nonlinear modeling, linear controller design, nonlinear simulation and flight test but uses an indoor-installed multi-camera system, which can provide full 6-degree of freedom (DOF) navigation information with high accuracy, to overcome the limitation of an outdoor flight experiment. In addition, a 3-DOF flying mill is used for the performance validation of the attitude control, which considers the characteristics of the multi-rotor type rotorcraft UAV. Our framework is applied to the design and mathematical modeling of the control system for a quad-rotor UAV, which was selected as the test-bed vehicle, and the controller design using the classical proportional-integral-derivative control method is explained. The experimental results showed that the proposed approach can be viewed as a successful tool in developing the controller of new rotorcraft UAVs with reduced cost and time.