• Journal of Institute of Control, Robotics and Systems
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• v.16 no.8
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• pp.771-779
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• 2010

This paper presents a method that integrates the geometric path tracking and the obstacle avoidance for nonholonomic mobile robot. The mobile robot follows the path by moving through the turning radius given from the pure pursuit method which is the one of the geometric path tracking methods. And the obstacle generates the obstacle potential, from this potential, the virtual force is obtained. Therefore, the turning radius for avoiding the obstacle is calculated by proportional to the virtual force. By integrating the turning radius for avoiding the obstacle and the turning radius for following the path, the mobile robot follows the path and avoids the obstacle simultaneously. The effectiveness of the proposed method is verified through the real experiments for path tracking only, static obstacle avoidance, dynamic obstacle avoidance.

• ETRI Journal
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• v.37 no.3
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• pp.617-625
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• 2015

In this paper, a steering control system for the path tracking of autonomous vehicles is described. The steering control system consists of a path tracker and primitive driver. The path tracker generates the desired steering angle by using the look-ahead distance, vehicle heading, and a lateral offset. A method for applying an autonomous vehicle to path tracking is an advanced pure pursuit method that can reduce cutting corners, which is a weakness of the pure pursuit method. The steering controller controls the steering actuator to follow the desired steering angle. A servo motor is installed to control the steering handle, and it can transmit the steering force using a belt and pulley. We designed a steering controller that is applied to a proportional integral differential controller. However, because of a dead band, the path tracking performance and stability of autonomous vehicles are reduced. To overcome the dead band, a dead band compensator was developed. As a result of the compensator, the path tracking performance and stability are improved.

• Journal of Auto-vehicle Safety Association
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• v.13 no.2
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• pp.35-41
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• 2021

In this study, improved path tracking control algorithm based on pure pursuit algorithm is newly proposed by using improved lane detection algorithm through real time post-processing with interpolation methodology. Since the original pure pursuit works well only at speeds below 20 km/h, the look-ahead distance is implemented as a sigmoid function to work well at an average speed of 45 km/h to improve tracking performance. In addition, a smoothing filter was added to reduce the steering angle vibration of the original algorithm, and the stability of the steering angle was improved. The post-processing algorithm presented has implemented more robust lane recognition system using real-time pre/post processing method with deep learning and estimated interpolation. Real time processing is more cost-effective than the method using lots of computing resources and building abundant datasets for improving the performance of deep learning networks. Therefore, this paper also presents improved lane detection performance by using the final results with naive computer vision codes and pre/post processing. Firstly, the pre-processing was newly designed for real-time processing and robust recognition performance of augmentation. Secondly, the post-processing was designed to detect lanes by receiving the segmentation results based on the estimated interpolation in consideration of the properties of the continuous lanes. Consequently, experimental results by utilizing driving guidance line information from processing parts show that the improved lane detection algorithm is effective to minimize the lateral offset error in the diverse maneuvering roads.

• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.142-151
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• 2022

With the advent of the 4th industrial revolution, autonomous driving technology is being commercialized in various industries. However, research on autonomous driving so far has focused on platforms with wheel-type platform. Research on a tracked platform is at a relatively inadequate step. Since the tracked platform has a different driving and steering method from the wheel-type platform, the existing research cannot be applied as it is. Therefore, a path-tracking algorithm suitable for a tracked platform is required. In this paper, we studied a path-tracking algorithm for a tracked platform based on a GPS sensor. The existing Pure Pursuit algorithm was applied in consideration of the characteristics of the tracked platform. And to compensate for "Cutting Corner", which is a disadvantage of the existing Pure Pursuit algorithm, an algorithm that changes the LAD according to the curvature of the path was developed. In the existing pure pursuit algorithm that used a tracked platform to drive a path including a right-angle turn, the RMS path error in the straight section was 0.1034 m and the RMS error in the turning section was measured to be 0.2787 m. On the other hand, in the variable LAD algorithm, the RMS path error in the straight section was 0.0987 m, and the RMS path error in the turning section was measured to be 0.1396 m. In the turning section, the RMS path error was reduced by 48.8971%. The validity of the algorithm was verified by measuring the path error by tracking the path using a tracked robot platform.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.18-20
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• 2021

In order to prevent collision accidents of ships, which has been increasing recently, research on artificial intelligence-based autonomously operated ships (Maritime Autonomous Surface Ship, MASS) is underway. However, most of the studies related to autonomous ships mainly target medium-to-large ships due to the size and cost of the autonomous navigation system, and the sensors used here have a problem in that it is difficult to mount them on small ships. Therefore, this paper provides a path tracking system equipped with GPS and IMU sensors for autonomous operation of small ships. GPS and IMU sensors are utilized to determine the exact position of the vessel, which allows the proposed system to manually control the small vessel model to create a path and then when the small vessel travels the same path. Use the Pure Pursuit algorithm to follow the path. As a result, In this research, it is expected that a lightweight and low-cost sensor can be used to develop an autonomous operation system for small ships at low cost.

• Journal of Ocean Engineering and Technology
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• v.30 no.3
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• pp.208-213
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• 2016

This paper proposes a potential field-based guidance law for docking a USV (unmanned surface vehicle). In most cases, a USV without side thrusters is an under-actuated system. Thus, there are undockable regions near docking stations where a USV cannot dock to a docking station without causing a collision or backward motion. This paper suggest a guidance law that prevents a USV from enter such a region by decreasing the lateral error to the docking station at the initial stage of the docking process. A Monte-carlo simulation was performed to validate the performance of the proposed method. The proposed method was compared to conventional guidance laws such as pure pursuit guidance and pure/lead pursuit guidance. As a result, the collision angle and lateral distance error of proposed method tended to have lower values compared to conventional methods.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.82.2-82
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• 2002

The new guidance law for a missile with the varying velocity after the rocket motor burned out is presented. This guidance is mechanized by combining the proportional navigation and the pure pursuit navigation. Some simulations are performed and then the simulation results show that the guidance law presented is effective even if the vehicle speed decreases significantly and has higher off-boresight ability than the proportional navigation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.11
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• pp.979-987
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• 2012

This paper implements and integrates algorithms for terrain following of UCAVs (Unmanned Combat Aerial Vehicles): trajectory generation, guidance, and navigation. Terrain following is very important for UCAVs because they perform very dangerous missions such as Suppression of Enemy Air Defences while the terrain following can improve the survivability of UCAVs against from the air defence systems of the enemy. To deal with the GPS jamming, terrain referenced navigation based on nonlinear filter is chosen. For the trajectory generation, Voronoi diagram is adopted to generate horizontal plane path to avoid the air defense system. Cubic spline method is used to generate vertical plane path to prevent collisions with ground while flying sufficiently close to surface. Follow-the-Carrot and pure pursuit tracking methods, which are look-ahead point based guidance algorithms, are applied for the guidance. Numerical simulation is performed to verify the performance of the integrated terrain following algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.10
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• pp.939-947
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• 2010

With the rising numbers of elderly and disabled people, the demand for welfare services using a robotic system and not involving human effort is likewise increasing. This study deals with a mobile-robot system combined with a BWS (Body Weight Support) system for gait rehabilitation. The BWS system is designed via the kinematic analysis of the robot's body-lifting characteristics and of the walking guide system that controls the total rehabilitation system integrated in the mobile robot. This mobile platform is operated by utilizing the AGV (Autonomous Guided Vehicle) driving algorithm. Especially, the method that integrates geometric path tracking and obstacle avoidance for a nonholonomic mobile robot is applied so that the system can be operated in an area where the elderly users are expected to be situated, such as in a public hospital or a rehabilitation center. The mobile robot follows the path by moving through the turning radius supplied by the pure-pursuit method which is one of the existing geometric path-tracking methods. The effectiveness of the proposed method is verified through the real experiments those are conducted for path tracking with static- and dynamic-obstacle avoidance. Finally, through the EMG (Electromyography) signal measurement of the subject, the performance of the proposed system in a real operation condition is evaluated.

• Journal of Applied and Pure Mathematics
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• v.5 no.5_6
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• pp.389-406
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• 2023

In the pursuit of enhancing image fusion techniques, this research presents a novel approach for fusing multimodal images, specifically infrared (IR) and visible (VIS) images, utilizing a combination of partial differential equations (PDE) and discrete cosine transformation (DCT). The proposed method seeks to leverage the thermal and structural information provided by IR imaging and the fine-grained details offered by VIS imaging create composite images that are superior in quality and informativeness. Through a meticulous fusion process, which involves PDE-guided fusion, DCT component selection, and weighted combination, the methodology aims to strike a balance that optimally preserves essential features and minimizes artifacts. Rigorous evaluations, both objective and subjective, are conducted to validate the effectiveness of the approach. This research contributes to the ongoing advancement of multimodal image fusion, addressing applications in fields like medical imaging, surveillance, and remote sensing, where the marriage of IR and VIS data is of paramount importance.