Environmental Recognition for Autonomous Robot using Simultaneous Localization and Map Building (SLAM) (Real Time Path Planning with Dynamical Localized Voronoi Division)

Takezawa, Satoshi; Gulrez, Tauseef; Herath, Damith; Dissanayake, Gamini

doi:10.1299/kikaic.71.904

Cited by 5 publications

(3 citation statements)

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“…Automatic driving is a complex process, and it is also a process of self-learning which includes environmental recognition, real time localization, path planning and motion tracking control [ 18 , 19 , 20 , 21 , 22 ]. In this case, soft computing techniques provide the advantage of representing expert knowledge for controlling complex and nonlinear processes, such as autonomous driving.…”

Section: Introductionmentioning

confidence: 99%

The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network

Gai-ning

Wen

et al. 2017

Sensors

124

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The intelligent vehicle is a complicated nonlinear system, and the design of a path tracking controller is one of the key technologies in intelligent vehicle research. This paper mainly designs a lateral control dynamic model of the intelligent vehicle, which is used for lateral tracking control. Firstly, the vehicle dynamics model (i.e., transfer function) is established according to the vehicle parameters. Secondly, according to the vehicle steering control system and the CARMA (Controlled Auto-Regression and Moving-Average) model, a second-order control system model is built. Using forgetting factor recursive least square estimation (FFRLS), the system parameters are identified. Finally, a neural network PID (Proportion Integral Derivative) controller is established for lateral path tracking control based on the vehicle model and the steering system model. Experimental simulation results show that the proposed model and algorithm have the high real-time and robustness in path tracing control. This provides a certain theoretical basis for intelligent vehicle autonomous navigation tracking control, and lays the foundation for the vertical and lateral coupling control.

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Section: Introductionmentioning

confidence: 99%

The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network

Gai-ning

Wen

et al. 2017

Sensors

124

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“…So far, Voronoi partitions were studied for applications to the formation control. Takezawa and colleagues proposed a method of planning the travel path of an autonomous robot in a space with unknown obstacles by extracting successive obstacles as characteristic points and by dividing the space into Voronoi regions using the characteristic point as the base [12]. Matsumoto and colleagues proposed to plan safe and smooth travel paths for carlike robots to avoid obstacles by determining obstacle boundaries by the Voronoi partitions and by connecting these paths by the clothoid curve [13].…”

Section: Introductionmentioning

confidence: 99%

Deployment control of wireless multihop‐relay mobile robots based on voronoi partition

Imaizumi

Murakami

Uchimura

2013

Electrical Engineering Japan

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SUMMARYThis paper describes a new method for the deployment of wireless relay nodes. When using rescue robots in a building or underground city, radio signals are attenuated significantly, and therefore, multihop extension involving wireless communication relays is required. The goal of this research is to deploy wireless relay nodes to maintain connectivity between the base station and the leader robot that explores around the front line. To move the relay robot autonomously, a distributed algorithm is required.The proposed method is suitable when it is applied for wireless relay purposes. In this method, a virtual force drives a node to the centroid of Voronoi neighbors so that the connectivity of wireless communication is maintained. The proposed method is evaluated by conducting numerical simulations and experiments. In the simulation, one or two leader robots are assumed. In the experiment, a mobile robot equipped with omni-wheels is used.

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“…The general SLAM problem has been the subject of substantial research in the past few years [1], [2] and [3]. SLAM using vision is becoming more and more important due to the recent developments in image processing.…”

Section: Introductionmentioning

confidence: 99%

Optimal Control for Simultaneous Localisation and Mapping Problems in Indoor Environments with Stereo Vision

Takezawa

Ishimoto

Dissanayake

2006

IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics

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This paper proposes a optimal control method for simultaneous localisation and mapping (SLAM) in an indoor environment using stereo vision. Specially designed artificial landmarks distributed in the environment are observed and extracted from a camera image. The disparity map obtained from the stereo vision system is used to obtain the ranges to these landmarks. The main contribution of the paper is the formulation of the mathematical framework for SLAM for a robot moving on a planar surface among landmarks distributed in three dimensional space. The paper also presents the results of experiments for optimal control conducted using a Pioneer robot and a Triclops stereo vision system. It is demonstrated that accurate robot and feature locations can be obtained using the proposed technique.

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Environmental Recognition for Autonomous Robot using Simultaneous Localization and Map Building (SLAM) (Real Time Path Planning with Dynamical Localized Voronoi Division)

Cited by 5 publications

References 0 publications

The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network

The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network

Deployment control of wireless multihop‐relay mobile robots based on voronoi partition

Optimal Control for Simultaneous Localisation and Mapping Problems in Indoor Environments with Stereo Vision

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