• Proceedings of the IEEK Conference
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• 2001.06e
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• pp.127-130
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• 2001

In this paper, we describes a method of estimating traveling direction of a autonomous vehicle. For the development of autonomous vehicle, it is important to detect road lane and to reckon traveling direction. The object of a propose algorithm is to perform lane detection in real-time for standalone vision system. And we calculate efficent traveling direction to find steering angie for lateral control system. Therefore autonomous vehicle go forward the center of lane by adjusting the current steering angle using traveling direction.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11c
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• pp.690-697
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• 2000

The objective of this study is to develop a method that is able to realize autonomous traveling for tractor-like robot on the slope terrain. A neural network (NN) and genetic algorithms (GAs) have been used for resolving nonlinear problems in this system. The NN is applied to create a vehicle simulator that is capable to describe the motion of the tractor robot on the slope, while it is impossible by the common dynamics way. Using this vehicle simulator, a control law optimized by GAs was established and installed in the computer to control the steering wheel of tractor robot. The autonomous traveling carried out on a 14-degree slope had initial successful results.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.31-32
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• 2012

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.211-217
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• 2014

This paper addresses an algorithm of path planning for autonomous driving of a ground vehicle in waypoint navigation. The proposed algorithm is flexible in utilization under a large GPS positioning error and generates collision-free multiple paths while pursuing minimum traveling time. An optimal path reduces inefficient steering by minimizing lateral changes in generated waypoints along a path. Simulation results compare the proposed algorithm with the A* algorithm by manipulation of the steering wheel and traveling time, and show that the proposed algorithm realizes real-time obstacle avoidance by quick processing of path generation, and minimum time traveling by producing paths with small lateral changes while overcoming the very irregular positioning error from the GPS.

• Korean Journal of Agricultural Science
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• v.37 no.1
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• pp.113-121
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• 2010

Land consolidation ratio for rice paddy fields reached to 64.7% as of 2008 in Korea, and this also accelerated automation of field machinery. Especially, research on autonomous tractors has been continuously conducted. Tillage is one of the labor-, energy-, and time-consuming field operations. Most important requirements for autonomous tractors would be travelling path planning and electronic system to control the tractor to follow the path. The instruction of computer was required to conduct the tillage operation in field with unmanned traveling tractor. This instruction was coincidently used in the control of the traveling path and the motion of tractor. The objectives of the study were 1) to characterize and model tillage operating sequence, turning pattern, and 2) to develop tillage path formation programs for autonomous tractor and evaluate the performance.

• Journal of Drive and Control
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• v.19 no.4
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• pp.19-28
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• 2022

This paper introduces an automatic steering system for straight traveling capable of being mounted on drivable agricultural machinery which user can handle it such as a tractor, a transplant, etc. The modular automatic steering device proposed in the paper is composed of RTK GNSS, IMU, HMI, hydraulic valve, and wheel sensor. The path generation method of the automatic steering system is obtained from two location information(latitude and longitude on each point) measured by GNSS in advance. From HMI, a straight path(AB line) can be created by connecting latitude and longitude on each point and the device makes the machine able to follow the path. During traveling along the reference path, it acquires the real time position data every sample time(0.1s), compares the reference with them and calculates the lateral deviation. The values of deviation are used to control the steering angle of the machine using hydraulic valve mounted on the axle of front wheel. In this paper, Pure Pursuit algorithm is applied used in autonomous vehicles frequently. For the analysis of traveling characteristics, field tests were executed about these conditions: velocity of 2, 3, 4km/h which is applied to general agricultural work and ground surface of solid(asphalt) and weak condition(soil) such as farmland. In the case of weak ground state, two experiments were executed about no-load(without work) and load(with work such as plowing). The maximum average deviations were presented 2.44cm, 7.32cm, and 11.34cm during traveling on three ground conditions : asphalt, soil without load and with load(plowing).

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.217-225
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• 2016

In this paper, we propose an improved path planning method and obstacle avoidance algorithm for two-wheel mobile robots, which can be effectively applied in an environment where obstacles can be represented by circles. Firstly, we briefly introduce the rapidly exploring random tree (RRT) and single polar polynomial (SPP) algorithm. Secondly, we present additional two methods for applying our proposed method. Thirdly, we propose a global path planning, smoothing and obstacle avoidance method that combines the RRT and SPP algorithms. Finally, we present a simulation using our proposed method and check the feasibility. This shows that proposed method is better than existing methods in terms of the optimality of the trajectory and the satisfaction of the kinematic constraints.

• Korean Journal of Agricultural Science
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• v.38 no.2
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• pp.343-347
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• 2011

Precise traveling and tillage operation using an autonomous tractor is difficult with the data from the Geographic Information System(GIS) because it does not include the data of the width and inclination of the field to work. The minimum turing radius of the tractor could be different from the value presented by the tractor maker due to the moisture content of the field soil or operators' skill. Two programs were developed to process data obtained with the tillage path measuring system: one for recognizing coordinates of the 4 field corners, and the other for recognizing the minimum turning radius of the tractor.

• Korean Journal of Agricultural Science
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• v.37 no.1
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• pp.123-130
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• 2010

A steering control system based on CAN(Controller Area Network) for autonomous tractor was developed to reduce duty of a central processing computer and to improve performance of steering control in terms of reduced control interval and error. The steering control system consisted of a SCU (Steering Control Unit), an EHPS system, and a potentiometer. The SCU consisted of an MCU (Micro Controller unit), an A/D converter, and a DC-DC converter, and a PID controller was used to control steering angle. The steering control system was communicated with the computer by CAN-bus. Each actuator and implement was connected to a multi-function board interfacing with the computer through a USB cable. Without CAN, control interval of the autonomous tractor was 1.5 seconds. When the CAN-based steering control system was combined with the autonomous tractor, however, control interval of the integrated system was reduced to those less than 0.05 seconds. When the autonomous tractor was operated with 1.5-s and 0.05-s control cycles at a 0.63-m/s travelling speed, the trajectories were close to straight lines for both of the control cycles. For a 1.34-m/s traveling speed, tractor trajectory was close to sine wave with a 1.5-s control cycle, but was straight line with a 0.05-s control cycle.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.4
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• pp.767-779
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• 2017

Automated mission planning for unmanned aerial vehicles (UAVs) is difficult because of the propagation of several sources of error into the solution, as for any large scale autonomous system. To ensure reliable system performance, we quantify all sources of error and their propagation through a mission planner for operation of UAVs in an obstacle rich environment we developed in prior work. In this sequel to that work, we show that the mission planner developed before can be made robust to errors arising from the mapping, sensing, actuation, and environmental disturbances through creating systematic buffers around obstacles using the calculations of uncertainty propagation. This robustness makes the mission planner truly autonomous and scalable to many UAVs without human intervention. We illustrate with simulation results for trajectory generation of multiple UAVs in a surveillance problem in an urban environment while optimizing for either maximal flight time or minimal fuel consumption. Our solution methods are suitable for any well-mapped region, and the final collision free paths are obtained through offline sub-optimal solution of an mTSP (multiple traveling salesman problem).