• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.1
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• pp.57-67
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• 2015

A large amount of work has been done in the areas of routing, MAC, QoS, capacity, location service, cooperative communication, fault tolerance, mobility models and various applications of mesh networks thanks to their merits of cost-effective way of deployment and flexibility in extending wireline services. Although multi-path routing protocols have been proposed to be used to provide QoS and fault-tolerance, there has not been any significant results discussed that support both in the literature to our best knowledge as they are often required in military and public safety applications. In this paper, we present a novel routing protocol for a mesh network based on the OFDM-TDMA collision-free MAC that discovers and maintains multiple paths that allows retransmitting and forwarding packets that have been blocked due to a link failure using an alternative next-hop node such that the delay-capacity tradeoff is reduced and the reliability is enhanced. Simulation results show that the proposed protocol performs well in terms of both the QoS and delivery ratio.

• Journal of Aerospace System Engineering
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• v.18 no.2
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• pp.56-63
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• 2024

As the safety of unmanned vehicles continues to improve, their usage in urban environments, which are full of obstacles such as buildings, is expected to increase. When numerous unmanned vehicles are operated in such environments, an algorithm that takes into account mutual collision avoidance, as well as static and dynamic obstacle avoidance, is necessary. In this paper, we propose an algorithm that handles task assignment and path planning. To efficiently plan paths, we construct a grid-based map and derive the paths from it. To enable quick re-planning in dynamic environments, we focus on reducing computational time. Through simulation, we explain obstacle avoidance and mutual collision avoidance in small-scale problems and confirm their performance by observing the entire mission completion time (Makespan) in large-scale problems.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.168-173
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• 2003

In this paper, we will present a deeper look on optimal design methods that are related to path-planning for a mobile robot. To control the motion of a mobile robot in a clustered environment, it's necessary to know a suitable trajectory assuming certain start and goal point. Up to now, there are many literatures that concern optimal path planning for an obstacle avoided mobile robot. Among those literatures, we have chosen 2 novel methods for our further analysis. The first approach [4] is based on HJB(Hamilton-Jacobi-Bellman) equation whose solution is the return-function that helps to generate a shortest path to the goal. The later [5] is called polynomial-path-planning approach, in this method, a shortest polynomial-shape path would become a solution if it was a collision-free path. The camera network plays the role as sensors to generate updated map which locates the static and dynamic objects in the space. Therefore, the exhibition of both path planning and dynamic obstacle avoidance by the updated map would be accomplished simultaneously. As we mentioned before, our research will include the motion control of a true mobile robot on those optimal planned paths which were generated by above algorithms. Base on the kinematic and dynamic simulation results, we can realize the affection of moving speed to the stable of motion on each generated path. Also, we can verify the time-optimal trajectory through velocity tuning. To simplify for our analysis, we assumed the obstacles are cylindrical circular objects with the same size.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.5
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• pp.295-301
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• 2017

Recently, autonomous navigation technology, obstacle recognition, and obstacle collision avoidance technology are actively being developed for an unmanned surface vehicle (USV). The path to move from the current location to the destination should be planned, in order for an USV to autonomously operate safely to its destination. The dynamic window approach (DWA) is a well-known navigation scheme as a local path planning. The DWA algorithm derives the linear velocity and angular velocity by evaluating the destination direction, velocity, and distance from the obstacle. However, because DWA algorithm does not consider tracking the path, when using only the DWA algorithm, the ship may navigate away from the path line after avoiding obstacles. In this paper, we propose an improved DWA algorithm that can follow path line. And we implemented the simulation and compared the existing DWA algorithm with the improved DWA algorithm proposed in this paper. As a result, it is confirmed that the proposed DWA algorithm follows the path line better.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1483-1490
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• 2009

This parer is presented multiple path-planning of unmanned autonomous forklift using modified genetic algorithm and fuzzy inference system. There are a task-level feedback method and a method that path is dynamically replaned in realtime while the autonomous vehicles are moving by means of an optimal algorithm for existing multiple path-planning. However, such methods cause malfunctions and inefficiency in the sense of time and energy, and path-planning should be dynamically replanned in realtime. To solve these problems, we propose multiple path-planning using modified genetic algorithm and fuzzy inference system and show the performance with autonomous vehicles. For experiment, we designed and built two autonomous mobile vehicles that equipped with the same driving control part used in actual autonomous forklift, and test the proposed multiple path-planning algorithm. Experimental result that actual autonomous mobile vehicle, we verified that fast optimized path-planning and efficient collision avoidance are possible.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.6 s.312
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• pp.1-8
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• 2006

Many researches on path planning and obstacle avoidance for the fundamentals of mobile robot have been done recently. Informations from various sensors can be used to find obstacles and plan feasible path. In spite of many solutions of finding optimal path, each can be applied in only a constrained condition. This means that it is difficult to find university good algorithm. An optimal path with a complicated computation generates a time delay which cannot avoid moving obstacles. In this paper, we propose an algorithm of path planning and obstacle avoidance for mobile robot. We call the proposed method Random Access Sequence(RAS) method. In the proposed method, a small region is set first and numbers are assigned to its neighbors, then the path is selected using these numbers and cumulative numbers. It has an advantage of fast planning time and completeness of path if one exists. This means that new path selection may be possible within short time and that helps a robot to avoid obstacle in dynamic environments. Using the information of the start and destination position, the RAS can be performed for collision-free navigation by reforming feasible paths repeatedly in dynamic environments.

• The Journal of Korea Robotics Society
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• v.15 no.2
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• pp.100-106
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• 2020

In the agricultural field, interests in research using robots for fruit harvesting are continuously increasing. Dual arm manipulators are promising because of its abilities like task-distribution and role-sharing. To operate it efficiently, the task sequence must be planned adequately. In our previous study, a collision-free path planning method based on a genetic algorithm is proposed for dual arm manipulators doing tasks cooperatively. However, in order to simplify the complicated collision-check problem, the movement between tasks of two robots should be synchronized, and thus there is a problem that the robots must wait and resume their movement. In this paper, we propose a heuristic algorithm that can reduce the total time of the optimal solution obtained by using the previously proposed genetic algorithm. It iteratively desynchronizes the task sequence of two robots and reduces the waiting time. For evaluation, the proposed algorithm is applied to the same work as the previous study. As a result, we can obtain a faster solution having 22.57 s than that of the previous study having 24.081 s. It will be further studied to apply the proposed algorithm to the fruit harvesting.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.5
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• pp.1002-1012
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• 2003

An algorithm is suggested for collision avoidance of two-arm robot manipulator using redundancy. End-effectors of each redundant arm should move along each prescribed straight path to complete the given task, while avoiding collision with each other. Self-motion, considered as motion of each axis not to change the position and orientation of end-effector, is utilized in order to solve this problem. At each sampling time, self-motion is executed with the view to making farther between the links of each arm. Simulation results for two-arm robot manipulator, which has 9-d.o.f. respectively, are illustrated to show the performance of the algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.609-610
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• 2017

Cognitive radio communication techniques have been attracting attention to efficiently use the scarce spectrum as the wireless communication service increases. In cognitive radio communication, efforts to minimize interference to the primary user are important technical factors. In a multi-hop wireless ad hoc network, multi-hop transmission requires path and channel selection considering channel interference as well as collision with primary users. In the multi-channel environment, cognitive radio network has different capacities depending on the inter-channel interference and collision with the main users. In this paper, we propose a multi-hop transmission scheme that minimizes inter-channel interference and reduce collision with primary users.

• Journal of Auto-vehicle Safety Association
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• v.15 no.1
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• pp.35-44
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• 2023

The purpose of this study is to predict how the actual accident changes by reconstructing the accident with an Autonomous Emergency Braking system (AEB) based on the actual accident of the LTAP-OD (Left Turn Crossing Path - Opponent Direction) intersection. A virtual AEB sensor was developed, and 150 head-on collision accident reports were secured to the insurance company to reconstruct the accident. As a result of the accident type analysis, a total of 13 types of head-on collision accidents were derived, and it is the LTAP-OD intersection accident with the highest frequency. In the LTAP-OD intersection accident, the simulation was conducted by applying the virtual AEB of each vehicle, the accident rate decreased by 90% or more when the AEB of the left-turn vehicle was applied, and the accident rate decreased by 50%. In addition, the most frequent collision types in LTAP-OD accidents were the front bumper on the driver's side of a vehicle going straight and the front bumper on the passenger's side of a vehicle turning left.