scholarly journals A Low-Cost Consistent Vehicle Localization Based on Interval Constraint Propagation

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Zhan Wang ◽  
Alain Lambert
Keyword(s):  
Constraint Satisfaction Problem ◽  
Low Cost ◽  
Dead Reckoning ◽  
Constraint Propagation ◽  
Vehicle Localization ◽  
Practical Applications ◽  
Localization And Mapping ◽  
Position And Orientation ◽  
Map Data ◽  
Interval Constraint

Probabilistic techniques (such as Extended Kalman Filter and Particle Filter) have long been used to solve robotic localization and mapping problem. Despite their good performance in practical applications, they could suffer inconsistency problems. This paper proposes an interval analysis based method to estimate the vehicle pose (position and orientation) in a consistent way, by fusing low-cost sensors and map data. We cast the localization problem into an Interval Constraint Satisfaction Problem (ICSP), solved via Interval Constraint Propagation (ICP) techniques. An interval map is built when a vehicle embedding expensive sensors navigates around the environment. Then vehicles with low-cost sensors (dead reckoning and monocular camera) can use this map for ego-localization. Experimental results show the soundness of the proposed method in achieving consistent localization.

scholarly journals Dynamic ICSP Graph Optimization Approach for Car-Like Robot Localization in Outdoor Environments

Computers ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 63
Author(s):  
Zhan Wang ◽  
Alain Lambert ◽  
Xun Zhang
Keyword(s):  
Particle Filtering ◽  
Constraint Satisfaction Problem ◽  
Real Data ◽  
Constraint Propagation ◽  
Optimization Approach ◽  
Robot Localization ◽  
Data Set ◽  
Practical Applications ◽  
Outdoor Environments ◽  
Interval Constraint

Localization has been regarded as one of the most fundamental problems to enable a mobile robot with autonomous capabilities. Probabilistic techniques such as Kalman or Particle filtering have long been used to solve robotic localization and mapping problem. Despite their good performance in practical applications, they could suffer inconsistency problems. This paper presents an Interval Constraint Satisfaction Problem (ICSP) graph based methodology for consistent car-like robot localization in outdoor environments. The localization problem is cast into a two-stage framework: visual teach and repeat. During a teaching phase, the interval map is built when a robot navigates around the environment with GPS-support. The map is then used for real-time ego-localization as the robot repeats the path autonomously. By dynamically solving the ICSP graph via Interval Constraint Propagation (ICP) techniques, a consistent and improved localization result is obtained. Both numerical simulation results and real data set experiments are presented, showing the soundness of the proposed method in achieving consistent localization.

scholarly journals Localization of a Vehicle: A Dynamic Interval Constraint Satisfaction Problem-Based Approach

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Kangni Kueviakoe ◽  
Zhan Wang ◽  
Alain Lambert ◽  
Emmanuelle Frenoux ◽  
Philippe Tarroux
Keyword(s):  
Kalman Filter ◽  
Bayesian Methods ◽  
Constraint Satisfaction ◽  
Measurement Errors ◽  
Constraint Satisfaction Problem ◽  
Constraint Propagation ◽  
Gps Receiver ◽  
Localization Problem ◽  
Vehicle Localization ◽  
Interval Constraint

This paper introduces a new interval constraint propagation (ICP) approach dealing with the real-time vehicle localization problem. Bayesian methods like extended Kalman filter (EKF) are classically used to achieve vehicle localization. ICP is an alternative which provides guaranteed localization results rather than probabilities. Our approach assumes that all models and measurement errors are bounded within known limits without any other hypotheses on the probability distribution. The proposed algorithm uses a low-level consistency algorithm and has been validated with an outdoor vehicle equipped with a GPS receiver, a gyro, and odometers. Results have been compared to EKF and other ICP methods such as hull consistency (HC4) and 3-bound (3B) algorithms. Both consistencies of EKF and our algorithm have been experimentally studied.

Computation of Stability Margins for Uncertain Linear Fractional-Order Systems

2009 ◽  
Vol 132 (1) ◽  
Author(s):  
P. S. V. Nataraj ◽  
Rambabu Kalla
Keyword(s):  
Fractional Order ◽  
Constraint Satisfaction Problem ◽  
Constraint Propagation ◽  
Order System ◽  
Turbine Plant ◽  
Stability Margins ◽  
Propagation Technique ◽  
The Stability ◽  
Branch And Prune Algorithm ◽  
Interval Constraint

The present paper proposes an algorithm for finding the stability margins and cross over frequencies for an uncertain fractional-order system using the interval constraint propagation technique. It is first shown that the problem of finding the stability margins and crossover frequencies can be formulated as an interval constraint satisfaction problem and then solved using the branch and prune algorithm. The algorithm guarantees that the stability margins and the crossover frequencies are computed to the prescribed accuracy. The proposed algorithm is demonstrated on a noninductive cable system and also on a practical application of a gas turbine plant.

scholarly journals A Novel Underwater Simultaneous Localization and Mapping Online Algorithm Based on Neural Network

2019 ◽  
Vol 9 (1) ◽  
pp. 5 ◽  
Author(s):  
Guangchao Hou ◽  
Qi Shao ◽  
Bo Zou ◽  
Liwen Dai ◽  
Zhe Zhang ◽  
...  
Keyword(s):  
Online Algorithm ◽  
Low Cost ◽  
Autonomous Underwater Vehicles ◽  
Low Frequency ◽  
Dead Reckoning ◽  
Simultaneous Localization And Mapping ◽  
Low Complexity ◽  
Petroleum Engineering ◽  
Long Baseline ◽  
Localization And Mapping

The navigation and localization of autonomous underwater vehicles (AUVs) in seawater are of the utmost importance for scientific research, petroleum engineering, search and rescue, and military missions concerning the special environment of seawater. However, there is still no general method for AUVs navigation and localization, especially in the featureless seabed. The reported approaches to solving AUVs navigation and localization problems employ an expensive inertial navigation system (INS), with cumulative errors and dead reckoning, and a high-cost long baseline (LBL) in a featureless subsea. In this study, a simultaneous localization and mapping (AMB-SLAM) online algorithm, based on acoustic and magnetic beacons, was proposed. The AMB-SLAM online algorithm is based on multiple randomly distributed beacons of low-frequency magnetic fields and a single fixed acoustic beacon for location and mapping. The experimental results show that the performance of the AMB-SLAM online algorithm has a high robustness. The proposed approach (the AMB-SLAM online algorithm) provides a low-complexity, low-cost, and high-precision online solution to the AUVs navigation and localization problem in featureless seawater environments. The AMB-SLAM online solution could enable AUVs to autonomously explore or autonomously intervene in featureless seawater environments, which would enable AUVs to accomplish fully autonomous survey missions.

Stereo Vision Based Localization Method for Intelligent Vehicle

2013 ◽  
Vol 694-697 ◽  
pp. 1931-1936
Author(s):  
Feng Ping Cao ◽  
Rong Ben Wang ◽  
Liang Xiu Zhang
Keyword(s):  
Stereo Vision ◽  
Probability Model ◽  
Three Dimensional ◽  
Dead Reckoning ◽  
Intelligent Vehicle ◽  
Localization Algorithm ◽  
Vehicle Localization ◽  
Localization Method ◽  
Localization And Mapping ◽  
Slam Algorithm

In order to overcome the accumulated error in traditional localization methods for intelligent vehicle such as dead reckoning and visual odometry, a simultaneous localization and mapping(SLAM) algorithm based on stereo vision was presented in the paper. Firstly, the interrelated elements in the localization method were defined, and the probability model for intelligent vehicle localization was proposed, then the motion and observation model were established, and the detailed implementation of the introduced localization algorithm was given. Finally, an experiment was designed to confirm the effectiveness of the proposed method. Experimental results indicate that the algorithm can realize three-dimensional motion estimation of intelligent vehicle and can improve the positioning precision effectively.

Improved intelligent vehicle self-localization with integration of sparse visual map and high-speed pavement visual odometry

2020 ◽  
Vol 235 (1) ◽  
pp. 177-187
Author(s):  
Gang Huang ◽  
Zhaozheng Hu ◽  
Qianwen Tao ◽  
Fan Zhang ◽  
Zhe Zhou
Keyword(s):  
High Speed ◽  
Low Cost ◽  
Visual Odometry ◽  
Lateral View ◽  
Intelligent Vehicles ◽  
High Speed Camera ◽  
Vehicle Localization ◽  
Localization And Mapping ◽  
Resolution Imaging ◽  
Fundamental Requirement

Localization is a fundamental requirement for intelligent vehicles. Conventional localization methods usually suffer from various limitations, such as low accuracy and blocked areas for Global Positioning System, high cost for inertial navigation system or light detection and ranging, and low robustness for visual simultaneous localization and mapping or visual odometry. To overcome these problems, we propose a novel localization method integrated with a sparse visual map and a high-speed pavement visual odometry. We use a lateral-view camera to sense the sparse visual map node for accurate map-based localization. We use a down-view high-speed camera for odometry computation between two sparse visual map nodes. With a high-speed camera, it is possible to extract and track pavement features with stable resolution imaging even in high-speed movement. We also develop a data-driven motion model for the Kalman filter to fuse the localization results from the sparse map and the high-speed pavement visual odometry to enhance vehicle localization. The proposed method was tested in two different scenarios in different pavement conditions. The experimental results demonstrate that the proposed method can improve vehicle localization with low cost and high feasibility.

scholarly journals Chemical Modification of Combusted Coal Gangue for U(VI) Adsorption: Towards a Waste Control by Waste Strategy

2021 ◽  
Vol 13 (15) ◽  
pp. 8421
Author(s):  
Yuan Gao ◽  
Jiandong Huang ◽  
Meng Li ◽  
Zhongran Dai ◽  
Rongli Jiang ◽  
...  
Keyword(s):  
Structural Analysis ◽  
High Efficiency ◽  
Low Cost ◽  
Chemical Activation ◽  
Cost Effective ◽  
Coal Gangue ◽  
Order Kinetic ◽  
Practical Applications ◽  
Detailed Structural Analysis ◽  
Alkaline Conditions

Uranium mining waste causes serious radiation-related health and environmental problems. This has encouraged efforts toward U(VI) removal with low cost and high efficiency. Typical uranium adsorbents, such as polymers, geopolymers, zeolites, and MOFs, and their associated high costs limit their practical applications. In this regard, this work found that the natural combusted coal gangue (CCG) could be a potential precursor of cheap sorbents to eliminate U(VI). The removal efficiency was modulated by chemical activation under acid and alkaline conditions, obtaining HCG (CCG activated with HCl) and KCG (CCG activated with KOH), respectively. The detailed structural analysis uncovered that those natural mineral substances, including quartz and kaolinite, were the main components in CCG and HCG. One of the key findings was that kalsilite formed in KCG under a mild synthetic condition can conspicuous enhance the affinity towards U(VI). The best equilibrium adsorption capacity with KCG was observed to be 140 mg/g under pH 6 within 120 min, following a pseudo-second-order kinetic model. To understand the improved adsorption performance, an adsorption mechanism was proposed by evaluating the pH of uranyl solutions, adsorbent dosage, as well as contact time. Combining with the structural analysis, this revealed that the uranyl adsorption process was mainly governed by chemisorption. This study gave rise to a utilization approach for CCG to obtain cost-effective adsorbents and paved a novel way towards eliminating uranium by a waste control by waste strategy.

Sign in / Sign up

Export Citation Format

Share Document