• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3270-3294
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• 2020

Some things come easily to humans, one of them is the ability to navigate around. This capability of navigation suffers significantly in case of partial or complete blindness, restricting life activity. Advances in the technological landscape have given way to new solutions aiding navigation for the visually impaired. In this paper, we analyze the existing works and identify the challenges of path selection, context awareness, obstacle detection/identification and integration of visual and nonvisual information associated with real-time assisted mobility. In the process, we explore machine learning approaches for robotic path planning, multi constrained optimal path computation and sensor based wearable assistive devices for the visually impaired. It is observed that the solution to problem is complex and computationally intensive and significant effort is required towards the development of richer and comfortable paths for safe and smooth navigation of visually impaired people. We cannot overlook to explore more effective strategies of acquiring surrounding information towards autonomous mobility.

• Journal of Korea Game Society
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• v.6 no.3
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• pp.3-12
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• 2006

Path-finding, one of the traditional Game A.I. problems, becomes an important issue to make games more realistic. Due to the limited resources in the computer system, path-finding systems sometimes produce a simplified and unrealistic path. The most relent researches have been focused on the path-finding avoiding only static obstacles. Various moving obstacles are however deployed in real games, a method avoiding those obstacles and producing a smooth path is necessary. In this paper, navigation mesh is used to represent 3D space and its topological characteristics are used for path-finding. Intellectual repulser and attractor are also used to avoid moving obstacles and to find an optimal path. We have evaluated the path produced by the method proposed in this paper and verified its usability in real game.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.3
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• pp.203-209
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• 2010

This paper presents a hierarchical fuzzy motion planner for humanoid robots in 3D uneven environments. First, we define both motion primitives and locomotion primitives of humanoid robots. A high-level planner finds a global path from a global navigation map that is generated based on a combination of 2.5 dimensional maps of the workspace. We use a passage map, an obstacle map and a gradient map of obstacles to distinguish obstacles. A mid-level planner creates subgoals that help the robot efficiently cope with various obstacles using only a small set of locomotion primitives that are useful for stable navigation of the robot. We use a local obstacle map to find the subgoals along the global path. A low-level planner searches for an optimal sequence of locomotion primitives between subgoals by using fuzzy motion planning. We verify our approach on a virtual humanoid robot in a simulated environment. Simulation results show a reduction in planning time and the feasibility of the proposed method.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.11a
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• pp.256-257
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• 2018

This paper deals with the path-following control for marine surface vehicles with underactuated characteristics. In consideration of practical limitations of actuators, an improved DVS(dynamic virtual ship) guidance algorithm is proposed with the multi-level DVS optionally selected to be tracked. To address the output-feedback control issue, an adaptive FLS(fuzzy logical systems) is devised to online approximate the kinematic states. Based on that observing framework, the path-following control law is thereafter derived. Simulations testify effectiveness of the proposed scheme

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.6
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• pp.719-725
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• 2013

In this paper, we propose a local path planning method based on RANGER algorithm and autonomy manager for autonomous navigation of UGV in urban environment. LPP method is designed to generate the local path in sensing area by using lane and curb of pavement and autonomy manager is designed to make a decision which transit the status of LPP component to a proper status for current navigation environment. A field test is conducted with scenarios in real urban environment in which crossroad, crosswalk and pavement are included and the performance of proposed method is validated.

• The Journal of Korea Robotics Society
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• v.5 no.4
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• pp.302-308
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• 2010

A gradient method can provide a global optimal path in indoor environments. However, the optimal path can be often generated in narrow areas despite a sufficient wide area which lead to safe navigation. This paper presents a novel approach to path planning for safe navigation of a mobile robot. The proposed algorithm extracts empty regions using a ray-casting method and then generates temporary waypoints in wider regions in order to reach the goal fast and safely. The experimental results show that the proposed method can generate paths in the wide regions in most cases and the robot can reach the goal safely at high speeds.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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• pp.745-754
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• 2013

An efficient urban outdoor localization and navigation system is proposed for car-like robots. First an accurate outdoor localization method is suggested using line/arc features and 2.5D map matching with LRFs (Laser Range Finders), which can reduce the number of singular cases and increase accuracy. Also, path generation, path tracking, and path modification algorithms are proposed for navigation. All these algorithms are implemented on an electric scooter to construct an autonomous urban outdoor localization and navigation system. Experiments reveal the practicality of the proposed system.

• Spatial Information Research
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• v.21 no.2
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• pp.1-9
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• 2013

Recently many researches have focused on indoor navigation system. An optimal indoor navigation method can help people to find a path in large and complex buildings easily. However, some indoor navigation algorithms only calculate approximate routes based on spatial topology analysis, while others only use indoor road networks. However, both of them use only one of the spatial topology or network information. In this paper, we present a navigation method based on topology analysis and room internal networks for indoor navigation path. FT-Indoornavi (Flexible Topology Analysis Indoornavi) calculate internal routes based on spatial topology and internal path networks to support length-dependent and running-time optimal routing, which adapt to complex indoor environment and can achieve a better performance in comparison of Elastic algorithm and iNav.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3393-3412
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• 2017

As a main challenge in network virtualization, virtual network embedding problem is increasingly important and heuristic algorithms are of great interest. Aiming at the problems of poor correlation in node embedding and link embedding, long distance between adjacent virtual nodes and imbalance resource consumption of network components during embedding, we herein propose a two-stage virtual network embedding algorithm NA-PVNM. In node embedding stage, resource requirement and breadth first search algorithm are introduced to sort virtual nodes, and a node fitness function is developed to find the best substrate node. In link embedding stage, a path fitness function is developed to find the best path in which available bandwidth, CPU and path length are considered. Simulation results showed that the proposed algorithm could shorten link embedding distance, increase the acceptance ratio and revenue to cost ratio compared to previously reported algorithms. We also analyzed the impact of position constraint and substrate network attribute on algorithm performance, as well as the utilization of the substrate network resources during embedding via simulation. The results showed that, under the constraint of substrate resource distribution and virtual network requests, the critical factor of improving success ratio is to reduce resource consumption during embedding.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.2
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• pp.141-147
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• 2008

In this paper, we present one approach to achieve safe navigation in indoor dynamic environment. So far, there have been various useful collision avoidance algorithms and path planning schemes. However, those algorithms have a fundamental limitation that the robot can avoid only "visible" obstacles. In real environment, it is not possible to detect all the dynamic obstacles around the robot. There exist a lot of "occluded" regions due to the limitation of field of view. In order to avoid possible collisions, it is desirable to consider visibility information. Then, a robot can reduce the speed or modify a path. This paper proposes a safe navigation scheme to reduce the risk of collision due to unexpected dynamic obstacles. The robot's motion is controlled according to a hybrid control scheme. The possibility of collision is dually reflected to a path planning and a speed control. The proposed scheme clearly indicates the structural procedure on how to model and to exploit the risk of navigation. The proposed scheme is experimentally tested in a real office building. The presented result shows that the robot moves along the safe path to obtain sufficient field of view, while appropriate speed control is carried out.