• Journal of the Korean Society of Systems Engineering
• /
• v.18 no.2
• /
• pp.40-49
• /
• 2022

Remote-controlled and autonomous driving based on artificial intelligence are key elements required for unmanned combat vehicles. The required capability of such an unmanned combat vehicle should be expressed in reasonable required operational capability(ROC). To this end, in this paper, the requirements of an unmanned combat vehicle operated under a manned-unmanned teaming were analyzed. The functional requirements are remote operation and control, communication, sensor-based situational awareness, field environment recognition, autonomous return, vehicle tracking, collision prevention, fault diagnosis, and simultaneous localization and mapping. Remote-controlled and autonomous driving of unmanned combat vehicles could be achieved through the combination of these functional requirements. It is expected that the requirement analysis results presented in this study will be utilized to satisfy the military operational concept and provide reasonable technical indicators in the system development stage.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.14 no.5
• /
• pp.760-767
• /
• 2011

To strategically select the technology priority based on the understanding of technology development trends and prospects is very important. To provide such guidance for autonomous driving technology in unmanned ground combat vehicles, this report deals with followings; 1) The core technologies for autonomous driving are reviewed. 2) And domestic and foreign policies for relevant technology development are investigated. 3) Then, to estimate the technology development trend, the published patents and research papers are analyzed. 4) Based on those analyses, domestic technology level and development prospects are expected.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.20 no.6
• /
• pp.803-812
• /
• 2017

This paper proposes a local path planning method for stable autonomous driving in rough terrain. There are various path planning techniques such as candidate paths, star algorithm, and Rapidly-exploring Random Tree algorithms. However, such existing path planning has limitations to reflecting the stability of unmanned ground vehicles. This paper suggest a path planning algorithm that considering the stability of unmanned ground vehicles. The algorithm is based on the genetic algorithm and assumes to have probability based obstacle map and elevation map. The simulation result show that the proposed algorithm can be used for real-time local path planning in rough terrain.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.05a
• /
• pp.229-231
• /
• 2018

As autonomous vehicle technology has been gradually developed, robots that have introduced autonomous navigation systems have been actively involved in areas where there is a lot of livelihoods such as industrial sites and accident sites. For this reason, the unmanned transportation system equipped with the autonomous traveling system is widely used in harmful environments where human access is difficult. In addition, the introduction of the autonomous driving system reduces the collision and casualties that occur in a mobility environment like the industrial field, and it helps the efficient work process. In addition, autonomous driving vehicles can be handled more safely and quickly in a wider area by transmitting the surrounding environment of each vehicle to a server connected to each autonomous driving vehicle and passing it through the main server. In this paper, by utilizing V2X communication for autonomous unmanned forklift system, it can increase industrial workload, reduce loss of life and damage to property through wide area forklifts.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.42 no.1
• /
• pp.205-213
• /
• 2017

This paper is a study on the method to derive the functional level required for autonomous unmanned ground vehicle, one of the defense robots. Conventional weapon systems are not significantly affected by the operating environment, while defense robots exhibit different performance depending on the operating environment, even if they are on the same platform. If the performance of defense robot is different depending on operational environment, results of mission performance will be vary significantly. Therefore, it is necessary to clarify the level of function required by the military in order to research and develop most optimal defense robots. In this thesis, we propose a method to derive the required function level of unmanned ground vehicles, focusing on autonomous driving, one of the most vital functions of defense robots. Our results showed that the autonomous driving function depending intervention levels and evaluated functional sensitivity for autonomous driving of the unmanned vehicle using climate and topography as variables.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2010.11a
• /
• pp.723-724
• /
• 2010

• Journal of Auto-vehicle Safety Association
• /
• v.15 no.4
• /
• pp.6-15
• /
• 2023

This paper develops scenarios to evaluate the safety performance of Unmanned Ground Vehicle on military circumstances. The scenarios were created using Pegasus Project 6-layer format. These scenarios consist of straight road, curved road, merging road and crossroad. We adapt these scenarios to unpaved road. The characteristics of unpaved roads were divided into roughness, friction coefficient and road frequency. This adaption is validated via computer simulation. We observe the scan lines of vehicle become tangled of the straight road that make the cognitive abilities of the vehicle low and the lane-keeping is unable when vehicles entering curved off-roads over 40 km/h. The developed scenarios will contribute to enhancing stability from the perspective of introducing autonomous driving technology to Korean military.

• The Journal of Korea Robotics Society
• /
• v.18 no.1
• /
• pp.93-98
• /
• 2023

In this paper, the development of an autonomous electric vehicle for logistics with a robotic arm is introduced. The manual driving electric vehicle was converted into an electric vehicle platform capable of autonomous driving. For autonomous driving, an encoder is installed on the driving wheels, and an electronic power steering system is applied for automatic steering. The electric vehicle is equipped with a lidar sensor, a depth camera, and an ultrasonic sensor to recognize the surrounding environment, create a map, and recognize the vehicle location. The odometry was calculated using the bicycle motion model, and the map was created using the SLAM algorithm. To estimate the location of the platform based on the generated map, AMCL algorithm using Lidar was applied. A user interface was developed to create and modify a waypoint in order to move a predetermined place according to the logistics process. An A-star-based global path was generated to move to the destination, and a DWA-based local path was generated to trace the global path. The autonomous electric vehicle developed in this paper was tested and its utility was verified in a warehouse.

• Journal of Institute of Control, Robotics and Systems
• /
• v.20 no.12
• /
• pp.1181-1188
• /
• 2014

In this paper, we propose a novel concept foran unmanned delivery service using a cooperative heterogeneous unmanned system consisting of a self-driving car and an unmanned aerial vehicle (UAV). The proposed concept is suitable to deliver parcels in high-density and high-rise urban or residential areas. In order to achieve the proposed concept, we will develop acooperative heterogeneous unmanned system. Customers can order goods using a smartphone application and the order information, including the position of the customer and the order time, and the package is transported automatically by the unmanned systems. The system assigns the tasks suitable for each unmanned vehicle by analyzing it based on map information. Performance is validated by experiments consisting of autonomous driving and flight tests in a real environment. For more evaluation, the landing position error analysis is performed using circular error probability (CEP).

• Journal of the Korean Society for Precision Engineering
• /
• v.26 no.6
• /
• pp.74-80
• /
• 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.