• Title, Summary, Keyword: Traversability

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A Dynamic Modeling of 6×6 Skid Type Vehicle for Real Time Traversability Analysis over Curved Driving Path (곡선주행 실시간 주행성 분석을 위한 스키드 차량의 동역학 모델링)

  • Joo, Sang-Hyun;Lee, Ji-Hong
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.4
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    • pp.359-364
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    • 2012
  • Real-Time Traversability should be analyzed from the equiped sensors' data in real time for autonomous outdoor navigation. However, it is difficult to find out such traversability that considers the terrain roughness and the vehicle dynamics especially in case of skid type vehicle. The traversability based on real time dynamic analysis was proposed to solve such problem but in navigation with strait driving path. To adapt the method into the navigation with curved driving path, a path following controller should be incorporated into the dynamic model even though it cause the real time problem. In this paper, a dynamic model is proposed to solve the real time problem in the traversability analysis based on real time dynamic simualtion. The dynamic model contains the control dummy which is connected to the vehicle body with a universal joint to follow the curved path without controller. Simulation and experimental results on $6{\times}6$ articulated unmanned ground vehicle demonstrate the method's effectiveness and applicability into the traversability analysis on terrain with bumps.

Development of a Traversability Map for Safe Navigation of Autonomous Mobile Robots (자율이동로봇의 안전주행을 위한 주행성 맵 작성)

  • Jin, Gang-Gyoo
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.4
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    • pp.449-455
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    • 2014
  • This paper presents a method for developing a TM (Traversability Map) from a DTM (Digital Terrain Model) collected by remote sensors of autonomous mobile robots. Such a map can be used to plan traversable paths and estimate navigation speed quantitatively in real time for robots capable of performing autonomous tasks over rough terrain environments. The proposed method consists of three parts: a DTM partition module which divides the DTM into equally spaced patches, a terrain information module which extracts the slope and roughness of the partitioned patches using the curve fitting and the fractal-based triangular prism method, and a traversability analysis module which assesses traversability incorporating with extracted terrain information and fuzzy inference to construct a TM. The potential of the proposed method is validated via simulation works over a set of fractal DTMs.

A High-Speed Autonomous Navigation Based on Real Time Traversability for 6×6 Skid Vehicle (실시간 주행성 분석에 기반한 6×6 스키드 차량의 야지 고속 자율주행 방법)

  • Joo, Sang-Hyun;Lee, Ji-Hong
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.3
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    • pp.251-257
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    • 2012
  • Unmanned ground vehicles have important military, reconnaissance, and materials handling application. Many of these applications require the UGVs to move at high speeds through uneven, natural terrain with various compositions and physical parameters. This paper presents a framework for high speed autonomous navigation based on the integrated real time traversability. Specifically, the proposed system performs real-time dynamic simulation and calculate maximum traversing velocity guaranteeing safe motion over rough terrain. The architecture of autonomous navigation is firstly presented for high-speed autonomous navigation. Then, the integrated real time traversability, which is composed of initial velocity profiling step, dynamic analysis step, road classification step and stable velocity profiling step, is introduced. Experimental results are presented that demonstrate the method for a $6{\times}6$ autonomous vehicle moving on flat terrain with bump.

The Generation of Directional Velocity Grid Map for Traversability Analysis of Unmanned Ground Vehicle (무인차량의 주행성분석을 위한 방향별 속도지도 생성)

  • Lee, Young-Il;Lee, Ho-Joo;Jee, Tae-Young
    • Journal of the Korea Institute of Military Science and Technology
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    • v.12 no.5
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    • pp.549-556
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    • 2009
  • One of the basic technology for implementing the autonomy of UGV(Unmanned Ground Vehicle) is a path planning algorithm using obstacle and raw terrain information which are gathered from perception sensors such as stereo camera and laser scanner. In this paper, we propose a generation method of DVGM(Directional Velocity Grid Map) which have traverse speed of UGV for the five heading directions except the rear one. The fuzzy system is designed to generate a resonable traveling speed for DVGM from current patch to the next one by using terrain slope, roughness and obstacle information extracted from raw world model data. A simulation is conducted with world model data sampled from real terrain so as to verify the performance of proposed fuzzy inference system.

A Mobile Robot Path Planning based on the Terrain with Varing Degrees of Traversability (연속적으로 변화하는 Traversability를 고려한 Mobile 로봇의 경로계획)

  • Lee, S.C.;Choo, H.J.
    • Proceedings of the KIEE Conference
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    • pp.2315-2317
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    • 1998
  • There has been extensive efforts about robot path planning. Some major approaches are the roadmap approach, potential field approach and the cell decomposition approach. However, most of the path planning methods proposed so far based on above approaches consider the terrains filled with binary obstacles, i.e., if there exists an obstacle, robot simply cannot pass the location. In this paper, A mobile robot path planning method based on the cell decomposition technique for mobile robot that takes account of the terrain with varing degrees of travers-ability is discussed.

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Outdoor Localization of a Mobile Robot Using Weighted GPS Data and Map Information (가중화된 GPS 정보와 지도정보를 활용한 실외 이동로봇의 위치추정)

  • Bae, Ji-Hun;Song, Jae-Bok;Choi, Ji-Hoon
    • The Journal of Korea Robotics Society
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    • v.6 no.3
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    • pp.292-300
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    • 2011
  • Global positioning system (GPS) is widely used to measure the position of a vehicle. However, the accuracy of the GPS can be severely affected by surrounding environmental conditions. To deal with this problem, the GPS and odometry data can be combined using an extended Kalman filter. For stable navigation of an outdoor mobile robot using the GPS, this paper proposes two methods to evaluate the reliability of the GPS data. The first method is to calculate the standard deviation of the GPS data and reflect it to deal with the uncertainty of the GPS data. The second method is to match the GPS data to the traversability map which can be obtained by classifying outdoor terrain data. By matching of the GPS data with the traversability map, we can determine whether to use the GPS data or not. The experimental results show that the proposed methods can enhance the performance of the GPS-based outdoor localization.

Terrain Classification for Enhancing Mobility of Outdoor Mobile Robot (실외 주행 로봇의 이동 성능 개선을 위한 지형 분류)

  • Kim, Ja-Young;Lee, Jong-Hwa;Lee, Ji-Hong;Kweon, In-So
    • The Journal of Korea Robotics Society
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    • v.5 no.4
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    • pp.339-348
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    • 2010
  • One of the requirements for autonomous vehicles on off-road is to move stably in unstructured environments. Such capacity of autonomous vehicles is one of the most important abilities in consideration of mobility. So, many researchers use contact and/or non-contact methods to determine a terrain whether the vehicle can move on or not. In this paper we introduce an algorithm to classify terrains using visual information(one of the non-contacting methods). As a pre-processing, a contrast enhancement technique is introduced to improve classification of terrain. Also, for conducting classification algorithm, training images are grouped according to materials of the surface, and then Bayesian classification are applied to new images to determine membership to each group. In addition to the classification, we can build Traversability map specified by friction coefficients on which autonomous vehicles can decide to go or not. Experiments are made with Load-Cell to determine real friction coefficients of various terrains.

Obstacle Classification for Mobile Robot Traversability using 2-dimensional Laser Scanning (2차원 레이저 스캔을 이용한 로봇의 산악 주행 장애물 판단)

  • Kim, Min-Hee;Kwak, Kyung-Woon;Kim, Soo-Hyun
    • Journal of the Korea Institute of Military Science and Technology
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    • v.15 no.1
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    • pp.1-8
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    • 2012
  • Obstacle detection is much studied by using sensors such as laser, vision, radar and ultrasonic in path planning for UGV(Unmanned Ground Vehicle), but not much reported about its characterization. In this paper not only an obstacle classification method using 2-dimensional LMS(Laser Measurement System) but also a decision making method whether to avoid or traverse the obstacle is proposed. The basic idea of decision making is to classify the characteristics by 2D laser scanned data and intensity data. Roughness features are obtained by range data using a simple linear regression model. The standard deviations of roughness and intensity data are used as measures for decision making by comparing with those of reference data. The obstacle classification and decision making for the UGV can facilitate a short path to the target position and the survivability of the robot.

A Method for Virtual Lane Estimation based on an Occupancy Grid Map (장애물 격자지도 기반 가상차선 추정 기법)

  • Ahn, Seongyong
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.8
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    • pp.773-780
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    • 2015
  • Navigation in outdoor environments is a fundamental and challenging problem for unmanned ground vehicles. Detecting lane markings or boundaries on the road may be one of the solutions to make navigation easy. However, because of various environments and road conditions, a robust lane detection is difficult. In this paper, we propose a new approach for estimating virtual lanes on a traversable region. Estimating the virtual lanes consist of two steps: (i) we detect virtual road region through road model selection based on traversability at current frame and similarity between the interframe and (ii) we estimate virtual lane using the number of lane on the road and results of previous frame. To improve the detection performance and reduce the searching region of interests, we use a probability map representing the traversability of the outdoor terrain. In addition, by considering both current and previous frame simultaneously, the proposed method estimate more stable virtual lanes. We evaluate the performance of the proposed approach using real data in outdoor environments.

A kinect-based parking assistance system

  • Bellone, Mauro;Pascali, Luca;Reina, Giulio
    • Advances in robotics research
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    • v.1 no.2
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    • pp.127-140
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    • 2014
  • This work presents an IR-based system for parking assistance and obstacle detection in the automotive field that employs the Microsoft Kinect camera for fast 3D point cloud reconstruction. In contrast to previous research that attempts to explicitly identify obstacles, the proposed system aims to detect "reachable regions" of the environment, i.e., those regions where the vehicle can drive to from its current position. A user-friendly 2D traversability grid of cells is generated and used as a visual aid for parking assistance. Given a raw 3D point cloud, first each point is mapped into individual cells, then, the elevation information is used within a graph-based algorithm to label a given cell as traversable or non-traversable. Following this rationale, positive and negative obstacles, as well as unknown regions can be implicitly detected. Additionally, no flat-world assumption is required. Experimental results, obtained from the system in typical parking scenarios, are presented showing its effectiveness for scene interpretation and detection of several types of obstacle.