Vision System For Mobile Robot Research Articles

Development of an autonomous fog computing platform using control-theoretic approach for robot-vision applications

This paper presents the dynamic modelling and linear matrix inequality (LMI) based controller design of a distributed fog computing framework for real-time robot vision applications. A mobile robot vision system acquires the images from an application environment such as a warehouse, where articles are stacked in numerous racks. We characterise the mobile robot vision data (MRVD) using frames per second (FPS) and the image resolution. From the MRVD, object detection is performed by an open-source deep learning (DL) platform for detecting and localising various objects. However, with higher FPS together with high-resolution images, the processing time by the DL algorithm increases significantly. This necessitates the deployment of a distributed computing platform with several computing nodes. In this work, we deploy a distributed fog computing environment (DFCE) for the real-time object detection in an application environment.The processing time required to handle the MRVD is called the service time. However, for efficient auto-scaling performance, the mathematical model of the DFCE, taking into consideration the characteristics of the MRVD is necessary. In this context, we envisage the application of control theory to build the dynamic model of the DFCE. A Linear Parameter Varying (LPV) model is proposed for the DFCE with the service time as the output, the number of fog nodes as the input, and the characteristics of MRVD as the time-varying parameters. At first, an LPV model for the DFCE is derived using system identification, and the model is validated using the real-time test data. The LPV model is converted to a Polytopic LPV (PLPV) model for LMI based controller design. Finally, we develop and validate a Linear Matrix Inequality (LMI) based LPV controller to meet the service time constraints for a given application environment.For localisation and trajectory tracking with obstacle avoidance in the application environment, the mobile robot implements an Extended Kalman Filter (EKF) based simultaneous localisation and mapping (SLAM) and a bug-based path planning algorithm respectively. Finally, we present, detailed controller validation results illustrating the mobile robot navigation together with the auto-scaling control for the fog computing platform to modulate the service time.

Research on Vision System Calibration Method of Forestry Mobile Robots

Forestry mobile robots can effectively solve the problems of low efficiency and poor safety in the forestry operation process. To realize the autonomous navigation of forestry mobile robots, a vision system consisting of a monocular camera and two-dimensional LiDAR and its calibration method are investigated. First, the adaptive algorithm is used to synchronize the data captured by the two in time. Second, a calibration board with a convex checkerboard is designed for the spatial calibration of the devices. The nonlinear least squares algorithm is employed to solve and optimize the external parameters. The experimental results show that the time synchronization precision of this calibration method is 0.0082s, the communication rate is 23Hz, and the gradient tolerance of spatial calibration is 8.55e−07. The calibration results satisfy the requirements of real-time operation and accuracy of the forestry mobile robot vision system. Furthermore, the engineering applications of the vision system are discussed herein. This study lays the foundation for further forestry mobile robots research, which is relevant to intelligent forest machines.

Identification method of suspicious targets in submarine cable boundary based on multi-source data fusion

This paper studies a new all-round visualized cable zone monitoring system and target identification method. Specifically,a mobile robot vision system based on distributed control was designed for improving the efficiency of video processing. Secondly,the saliency measure based on background priors was used for image preprocessing and excluded the background regions which were less important. Finally,the recognition accuracy of the target was improved according to the dynamic template matching to images which had been processed. The experimental results show that the method can meet the requirements of real-time and veracity in the process of mobile robot’s target recognition,the method show good effectiveness.

New approach to enhancing the performance of cloud-based vision system of mobile robots

Mobile robots require real-time performance, high computation power, and a shared computing environment. Although cloud computing offers computation power, it may adversely affect real-time performance owing to network lag. The main objective of this study is to allow a mobile robot vision system to reliably achieve real-time constraints using cloud computing. A human cloud mobile robot architecture is proposed as well as a data flow mechanism organized on both the mobile robot and the cloud server sides. Two algorithms are proposed: (i) A real-time image clustering algorithm, applied on the mobile robot side, and (ii) A modified growing neural gas algorithm, applied on the cloud server side. The experimental results demonstrate that there is a 25% to 45% enhancement in the total response time, depending on the communication bandwidth and image resolution. Moreover, better performance in terms of data size, path planning time, and accuracy is demonstrated over other state-of-the-art techniques.

Combined Vision System for Mobile Robots

The article is devoted to examination of the method for formation of a panoramic image in conjunction with formation of detailed fragments of space objects for the vision systems of the mobile robots. As is known, navigation of the mobile robots often should take into account three coordinates in conjunction with a detailed analysis of the individual objects. It is a common assumption that a vision system operates with a certain set of specific objects, which must be prepared or in some way marked and allocated. The dynamic objects also should be taken into account in the field review. It is proposed that the formation of three-dimensional images of the space objects should be done by combining the stereoscopy methods and highlighting the structural aspect. In preparation of the materials for publication a system was considered which combines vision with a panoramic optoelectronic system, which implements the method of the structural illumination and stereovision, at the same time.

Mobile robot vision system using continuous laser scanning for industrial application

Purpose The purpose of this paper is the presentation and research of a novel robot vision system, which uses laser dynamic triangulation, to determine three-dimensional (3D) coordinates of an observed object. The previously used physical operation principle of discontinuous scanning method is substituted by continuous method. Thereby applications become possible that were previously limited by this discretization. Design/methodology/approach The previously used prototype No. 2, which uses stepping motors to realize a discontinuous laser scan, was substituted by the new developed prototype No. 3, which contains servomotors, to achieve a continuous laser scan. The new prototype possesses only half the width and turns out to be significantly smaller and therefore lighter than the old one. Furthermore, no transmissions are used, which reduce the systematic error of laser positioning and increase the system reliability. Findings By using a continuous laser scan method instead of discontinuous laser scan method, dead zones in the laser scanner field can be eliminated. Thereby, also by changing the physical operation principle, the implementation of applications is allowed, which previously was limited by the fixed step size or by the object distance under observation. By using servomotors instead of stepping motors, also a significant reduced positioning time can be accomplished maintaining the relative positioning error less than 1 per cent. Originality/value The originality is based on the substitution of the physical operation principle of discontinuous by continuous laser scan. The previously used stepping motors discretized the laser scanner field and thereby produced dead zones, where 3D coordinates cannot be detected. These stepping motors were substituted by servomotors to revoke these disadvantages and provide a continuous laser scan, where dead zones in the field of view get eliminated and the step response of the laser scanner accelerated.

1P1-C05 Multi-Kinect搭載ロボットによるRGB-D特徴に基づいた人物追従に関する研究(移動ロボットのための視覚)

1P1-C05 Multi-Kinect搭載ロボットによるRGB-D特徴に基づいた人物追従に関する研究(移動ロボットのための視覚)

1P1-C06 Image Feature-based Traversability Analysis for Mobile Robot Navigation in Outdoor Environment(Vision System for Mobile Robot)

1P1-C06 Image Feature-based Traversability Analysis for Mobile Robot Navigation in Outdoor Environment(Vision System for Mobile Robot)

A Motion Image Detection Method Based on the Inter-Frame Difference Method

Mobile robot vision system based on image information on environment, to make it automatic separation from obstacles and achieve precise mathematical description of obstacles, we construct detection model which combined by the frame difference method and background subtraction for target detection, comprehensive utilization of the main idea of three frame difference image method, the background subtraction and frame difference method combined to complement each other, thereby overcoming each other's weaknesses and improving the effect of target detection, experiment results show that this method can effectively improve the efficiency of target detection.

Omni-Directional Vision System for Mobile Robot Using Structured Lights

Vision system can obtain rich environmental information, and vision is one of the most important sensing methods for mobile robot navigation and positioning. An omni-directional vision system using laser illumination is presented. The system can obtain the distance information of the obstacles around the mobile robot by only one image. The principle of the vision system is expounded; the mapping relationship between the image plane and the laser plane is given based on the analysis of the system model. The system benefits from the advantages of the omni-directional vision and the structured light vision, such as large ranged environmental information, high precision and robustness, etc. Experimental results of measurement and map construction verify the vision system.

1P1-L05 眼球・頸部協調運動機能を有する移動ロボット用両眼視覚制御システム(移動ロボットのための視覚)

1P1-L05 眼球・頸部協調運動機能を有する移動ロボット用両眼視覚制御システム(移動ロボットのための視覚)

2P1-J06 LRFと全方位カメラを搭載した屋外移動車ロボットの人間認識および追従方法(移動ロボットのための視覚)

2P1-J06 LRFと全方位カメラを搭載した屋外移動車ロボットの人間認識および追従方法(移動ロボットのための視覚)

2P1-K11 画像場所認識と路面標示を用いた位置補正による自己位置推定法(移動ロボットのための視覚)

2P1-K11 画像場所認識と路面標示を用いた位置補正による自己位置推定法(移動ロボットのための視覚)

2P1-K10 移動ロボットの遠隔操作における合成超広角画像システムの盲点領域の活用(移動ロボットのための視覚)

2P1-K10 移動ロボットの遠隔操作における合成超広角画像システムの盲点領域の活用(移動ロボットのための視覚)

2P1-K07 3次元距離センサを用いた移動ロボットのための屋外環境認識(移動ロボットのための視覚)

2P1-K07 3次元距離センサを用いた移動ロボットのための屋外環境認識(移動ロボットのための視覚)

2P1-J09 カメラ画像内の特徴点から構成する四角形の重心を利用した屋外自律移動ロボットの姿勢制御(移動ロボットのための視覚)

2P1-J09 カメラ画像内の特徴点から構成する四角形の重心を利用した屋外自律移動ロボットの姿勢制御(移動ロボットのための視覚)

2P1-K08 3次元距離センサとエスパアンテナを用いた特定人物の発見と追跡(移動ロボットのための視覚)

2P1-K08 3次元距離センサとエスパアンテナを用いた特定人物の発見と追跡(移動ロボットのための視覚)

1P1-L13 画像に基づく制御による非ホロノミック移動ロボットのためのファジィ軌道追従法(移動ロボットのための視覚)

1P1-L13 画像に基づく制御による非ホロノミック移動ロボットのためのファジィ軌道追従法(移動ロボットのための視覚)

1P1-M02 確率推定を用いた画像のエッジを保存する画像フィルターの開発(移動ロボットのための視覚)

1P1-M02 確率推定を用いた画像のエッジを保存する画像フィルターの開発(移動ロボットのための視覚)

1P1-M06 Autonomous Object Search in 3D Environment Using Object Co-occurrence Graph(Vision System for Mobile Robot)

We demonstrate the effective object search in unknown 3D environment by using Object Co-occurrence Graph (OCG). The proposed OCG is automatically constructed from many word-tagging images provided by millions of Internet users. It describes the co-occurrence relations between objects. Since the small target object is difficult to be recognized due to insufficient image's resolution or occlusion problem, the finding of large objects which relate to particular target object will be more appropriate. This large object is so called cue object since it provides hints about target object's location. In our approach, robot solely depends on visual information; visual grid map and proposed object detectors, for its task. Moreover we also show that the employment of OCG can actually make the searching task become easier, reduce operating time, and minimize the robot's movement trajectory.