scholarly journals An Improved Extended Information Filter SLAM Algorithm Based on Omnidirectional Vision

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Jingchuan Wang ◽  
Weidong Chen
Keyword(s):  
High Reliability ◽  
Information Matrix ◽  
Omnidirectional Vision ◽  
Great Efficiency ◽  
Repeated Observations ◽  
Global Correlation ◽  
Information Filter ◽  
Wide Scale ◽  
Slam Algorithm ◽  
Omnidirectional Images

In the SLAM application, omnidirectional vision extracts wide scale information and more features from environments. Traditional algorithms bring enormous computational complexity to omnidirectional vision SLAM. An improved extended information filter SLAM algorithm based on omnidirectional vision is presented in this paper. Based on the analysis of structure a characteristics of the information matrix, this algorithm improves computational efficiency. Considering the characteristics of omnidirectional images, an improved sparsification rule is also proposed. The sparse observation information has been utilized and the strongest global correlation has been maintained. So the accuracy of the estimated result is ensured by using proper sparsification of the information matrix. Then, through the error analysis, the error caused by sparsification can be eliminated by a relocation method. The results of experiments show that this method makes full use of the characteristic of repeated observations for landmarks in omnidirectional vision and maintains great efficiency and high reliability in mapping and localization.

scholarly journals AN INDOOR SLAM METHOD BASED ON KINECT AND MULTI-FEATURE EXTENDED INFORMATION FILTER

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 327-332
Author(s):  
M. Chang ◽  
Z. Kang
Keyword(s):  
Point Cloud ◽  
Information Matrix ◽  
Depth Image ◽  
Point Cloud Data ◽  
A Posteriori ◽  
Cloud Data ◽  
Information Filter ◽  
Error Accumulation ◽  
Priori Information ◽  
Information Vector

Based on the frame of ORB-SLAM in this paper the transformation parameters between adjacent Kinect image frames are computed using ORB keypoints, from which priori information matrix and information vector are calculated. The motion update of multi-feature extended information filter is then realized. According to the point cloud data formed by depth image, ICP algorithm was used to extract the point features of the point cloud data in the scene and built an observation model while calculating a-posteriori information matrix and information vector, and weakening the influences caused by the error accumulation in the positioning process. Furthermore, this paper applied ORB-SLAM frame to realize autonomous positioning in real time in interior unknown environment. In the end, Lidar was used to get data in the scene in order to estimate positioning accuracy put forward in this paper.

Sparse Extended Information Filter for AUV SLAM: Insights into the Optimal Sparse Time

2013 ◽  
Vol 427-429 ◽  
pp. 1670-1673 ◽  
Author(s):  
Hao Zhang ◽  
Bo He ◽  
Ning Luan
Keyword(s):  
Autonomous Underwater Vehicle ◽  
Computation Time ◽  
Underwater Vehicle ◽  
Information Loss ◽  
Sea Trial ◽  
Time Consumption ◽  
Localization And Mapping ◽  
Information Filter ◽  
Slam Algorithm ◽  
And Storage

Sparse extended information filter-based simultaneous localization and mapping (SEIF-based SLAM) algorithm can reflect significant advantages in terms of computation time and storage memories. However, SEIF-SLAM is easily prone to overconfidence due to sparsification strategy. In this paper we will consider the time consumption and information loss of sparse operation, and get the optimal sparse time. In order to verify the feasibility of sparsification, a sea trial for autonomous underwater vehicle (AUV) C-Ranger was conducted in Tuandao Bay. The experimental results will show the improved algorithm is much more effective and accurate comparedwithothermethods.

scholarly journals Navigation of an Omnidirectional Mobile Robot by Teaching a Few Omnidirectional Images

2004 ◽  
Vol 16 (1) ◽  
pp. 80-89 ◽  
Author(s):  
Akihiro Matsumoto ◽  
◽  
Shoji Tsukuda ◽  
Gosuke Yoshita ◽  
Keyword(s):  
Mobile Robot ◽  
Error Compensation ◽  
Robot Navigation ◽  
Mobile Robot Navigation ◽  
Omnidirectional Vision ◽  
Positional Error ◽  
Positioning Accuracy ◽  
Omnidirectional Mobile Robot ◽  
Compensation Algorithm ◽  
Omnidirectional Images

We used an omnidirectional vision for navigating an omnidirectional mobile robot. We examined teaching algorithms by showing a few images for mobile robot navigation, and verified its feasibility through experiments. To improve positioning accuracy, we designed and tested a positional error compensation algorithm that fits omnidirectional images.

scholarly journals A Novel Robust Student’s t-Based Cubature Information Filter with Heavy-Tailed Noises

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Yongtao Shui ◽  
Xiaogang Wang ◽  
Wutao Qin ◽  
Yu Wang ◽  
Baojun Pang ◽  
...  
Keyword(s):  
Information Matrix ◽  
Wishart Distribution ◽  
Gaussian Form ◽  
Information Filter ◽  
Leibler Divergence ◽  
Heavy Tailed ◽  
Bayesian Approximation ◽  
Student’S T ◽  
Scale Matrix ◽  
Fixed Point Iterations

In this paper, a novel robust Student’s t-based cubature information filter is proposed for a nonlinear multisensor system with heavy-tailed process and measurement noises. At first, the predictive probability density function (PDF) and the likelihood PDF are approximated as two different Student’s t distributions. To avoid the process uncertainty induced by the heavy-tailed process noise, the scale matrix of the predictive PDF is modeled as an inverse Wishart distribution and estimated dynamically. Then, the predictive PDF and the likelihood PDF are transformed into a hierarchical Gaussian form to obtain the approximate solution of posterior PDF. Based on the variational Bayesian approximation method, the posterior PDF is approximated iteratively by minimizing the Kullback-Leibler divergence function. Based on the posterior PDF of the auxiliary parameters, the predicted covariance and measurement noise covariance are modified. And then the information matrix and information state are updated by summing the local information contributions, which are computed based on the modified covariance. Finally, the state, scale matrix, and posterior densities are estimated after fixed point iterations. And the simulation results for a target tracking example demonstrate the superiority of the proposed filter.

scholarly journals Adaptive Consensus-Based Unscented Information Filter for Tracking Target with Maneuver and Colored Noise

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3069 ◽  
Author(s):  
Li ◽  
Wang ◽  
Zheng
Keyword(s):  
State Estimation ◽  
Situation Awareness ◽  
Information Matrix ◽  
Estimation Method ◽  
Measurement Noise ◽  
Distributed State Estimation ◽  
Information Filter ◽  
Fading Factor ◽  
Stability And Accuracy ◽  
The Impact

Distributed state estimation plays a key role in space situation awareness via a sensor network. This paper proposes two adaptive consensus-based unscented information filters for tracking target with maneuver and colored measurement noise. The proposed filters can fulfill the distributed estimation for non-linear systems with the aid of a consensus strategy, and can reduce the impact of colored measurement noise by employing the state augmentation and measurement differencing methods. In addition, a fading factor that shrinks the predicted information state and information matrix can suppress the impact of dynamical model error induced by target maneuvers. The performances of the proposed algorithms are investigated by considering a target tracking problem using a space-based radar network. This shows that the proposed algorithms outperform the traditional consensus-based distributed state estimation method in aspects of tracking stability and accuracy.

scholarly journals Maneuvering Target Tracking Algorithm Based on Interacting Multiple Models

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Gannan Yuan ◽  
Wei Zhu ◽  
Wei Wang ◽  
Bo Yin
Keyword(s):  
Target Tracking ◽  
Nonlinear Filtering ◽  
Information Matrix ◽  
Multiple Models ◽  
Quick Response ◽  
Multiple Model ◽  
Maneuvering Target Tracking ◽  
Filtering Algorithm ◽  
Maneuvering Target ◽  
Information Filter

Aiming at improving the accuracy and quick response of the filter in nonlinear maneuvering target tracking problems, the Interacting Multiple Models Cubature Information Filter (IMMCIF) is proposed. In IMMCIF, the Cubature Information Filter (CIF) is brought into Interacting Multiple Model (IMM), which can not only improve the accuracy but also enhance the quick response of the filter. CIF is a multisensor nonlinear filtering algorithm; it evaluates the information vector and information matrix rather than state vector and covariance, which can reduce the error of nonlinear filtering algorithm. IMM disposes all the models simultaneously through Markov Chain, which can enhance the quick response of the filter. Finally, the simulation results show that the proposed filter exhibits fast and smooth switching when disposing different maneuver models; it performs better than the IMMCKF and IMMUKF on tracking accuracy.

Optimum modified ramp-stress ALT plan with competing causes of failure

2017 ◽  
Vol 34 (5) ◽  
pp. 733-746 ◽  
Author(s):  
Preeti Wanti Srivastava ◽  
Tanu Gupta
Keyword(s):  
Change Point ◽  
Fisher Information Matrix ◽  
High Reliability ◽  
Information Matrix ◽  
Stress Rate ◽  
Accelerated Life Test ◽  
Life Test ◽  
Optimal Plan ◽  
Content Type ◽  
Accelerated Life

Purpose Accelerated life test is undertaken to induce early failure in high-reliability products likely to last for several years. Most of these products are exposed to several fatal risk factors and fail due to one of them. Examples include solar lighting device with two failure modes: capacitor failure, and controller failure. It is necessary to assess each risk factor in the presence of other risk factors as each one cannot be studied in isolation. The purpose of this paper is to explore formulation of optimum time-censored accelerated life test model under modified ramp-stress loading when different failure causes have independent exponential life distributions. Design/methodology/approach The modified ramp-stress uses one test chamber in place of the various chambers used in the normal ramp-stress accelerate life test thus saving experimental cost. The stress-life relationship is modeled by inverse power law, and for each failure cause, a cumulative exposure model is assumed. The method of maximum likelihood is used for estimating design parameters. The optimal plan consists in finding out relevant experimental variables, namely, stress rate and stress rate change point(s). Findings The optimal plan is devised using D-optimality criterion which consists in finding out optimal stress rate and optimal stress rate change point by maximizing logarithm of determinant of Fisher information matrix to the base 10. This criterion is motivated by the fact that the volume of joint confidence region of model parameters is inversely proportional to square root of determinant of Fisher information matrix. The results of sensitivity analysis show that the plan is robust to small deviations from the true values of baseline parameters. Originality/value The model formulated can help reliability engineers obtain reliability estimates quickly of high-reliability products that are likely to last for several years.

The Design of Real-Time Power Detection System in Communication Equipment

2012 ◽  
Vol 605-607 ◽  
pp. 1063-1067
Author(s):  
Xian Jun Yi ◽  
Jun Xia Jiang ◽  
De Wen Guo ◽  
Di Feng Zhang
Keyword(s):  
Real Time ◽  
Software Design ◽  
Communication Systems ◽  
Detection System ◽  
High Reliability ◽  
Complex Environment ◽  
Wide Range ◽  
Core Components ◽  
Wide Scale ◽  
Communication Equipment

Communications equipments' voltage, current fluctuations and power changes will bring uncertain hazards in communication systems, monitoring each functional unit's power is necessary. However, communication equipment's power supply has characteristics such as high transient and wide-scale fluctuations, which increases the difficulty of monitoring the power output. This paper introduces a design of an accurate real-time detection of each functional unit's power in communications equipment. The design uses dedicated power detection chip LTC4151 as the core components of the power collection, the LTC4151 which has wide range and high DC voltage input can measure output power, determine and make alarm processing under the management of the micro-controller. The hardware and software design of system are described in detail. The design has high reliability which solved the problem of monitoring communication equipment's power under the complex environment with simple circuit.

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