scholarly journals LIDAR Scan Matching in Off-Road Environments

Robotics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 35 ◽  
Author(s):  
Hao Fu ◽  
Rui Yu
Keyword(s):  
Urban Environment ◽  
Real World ◽  
Performance Indicators ◽  
Fusion Algorithm ◽  
Scan Matching ◽  
Two Stage ◽  
Critical Step ◽  
Land Vehicle ◽  
Algorithm Comparison ◽  
Score Map

Accurately matching the LIDAR scans is a critical step for an Autonomous Land Vehicle (ALV). Whilst most previous works have focused on the urban environment, this paper focuses on the off-road environment. Due to the lack of a publicly available dataset for algorithm comparison, a dataset containing LIDAR pairs with varying amounts of offsets in off-road environments is firstly constructed. Several popular scan matching approaches are then evaluated using this dataset. Results indicate that global approaches, such as Correlative Scan Matching (CSM), perform best on large offset datasets, whilst local scan matching approaches perform better on small offset datasets. To combine the merits of both approaches, a two-stage fusion algorithm is designed. In the first stage, several transformation candidates are sampled from the score map of the CSM algorithm. Local scan matching approaches then start from these transformation candidates to obtain the final results. Four performance indicators are also designed to select the best transformation. Experiments on a real-world dataset prove the effectiveness of the proposed approach.

Personalised attraction recommendation for enhancing topic diversity and accuracy

2021 ◽  
pp. 016555152199980
Author(s):  
Yuanyuan Lin ◽  
Chao Huang ◽  
Wei Yao ◽  
Yifei Shao
Keyword(s):  
Real World ◽  
Information Overload ◽  
Two Stage ◽  
Misclassification Cost ◽  
Second Stage ◽  
Low Visibility ◽  
Recommendation Diversity ◽  
Optimisation Model ◽  
Definition Of ◽  
Improved Methods

Attraction recommendation plays an important role in tourism, such as solving information overload problems and recommending proper attractions to users. Currently, most recommendation methods are dedicated to improving the accuracy of recommendations. However, recommendation methods only focusing on accuracy tend to recommend popular items that are often purchased by users, which results in a lack of diversity and low visibility of non-popular items. Hence, many studies have suggested the importance of recommendation diversity and proposed improved methods, but there is room for improvement. First, the definition of diversity for different items requires consideration for domain characteristics. Second, the existing algorithms for improving diversity sacrifice the accuracy of recommendations. Therefore, the article utilises the topic ‘features of attractions’ to define the calculation method of recommendation diversity. We developed a two-stage optimisation model to enhance recommendation diversity while maintaining the accuracy of recommendations. In the first stage, an optimisation model considering topic diversity is proposed to increase recommendation diversity and generate candidate attractions. In the second stage, we propose a minimisation misclassification cost optimisation model to balance recommendation diversity and accuracy. To assess the performance of the proposed method, experiments are conducted with real-world travel data. The results indicate that the proposed two-stage optimisation model can significantly improve the diversity and accuracy of recommendations.

Local Graph Edge Partitioning

2021 ◽  
Vol 12 (5) ◽  
pp. 1-25
Author(s):  
Shengwei Ji ◽  
Chenyang Bu ◽  
Lei Li ◽  
Xindong Wu
Keyword(s):  
Real World ◽  
Graph Partitioning ◽  
Large Scale ◽  
Complete Information ◽  
Local Information ◽  
Experimental Results ◽  
Two Stage ◽  
Graph Computation ◽  
Local Graph ◽  
Edge Partitioning

Graph edge partitioning, which is essential for the efficiency of distributed graph computation systems, divides a graph into several balanced partitions within a given size to minimize the number of vertices to be cut. Existing graph partitioning models can be classified into two categories: offline and streaming graph partitioning models. The former requires global graph information during the partitioning, which is expensive in terms of time and memory for large-scale graphs. The latter creates partitions based solely on the received graph information. However, the streaming model may result in a lower partitioning quality compared with the offline model. Therefore, this study introduces a Local Graph Edge Partitioning model, which considers only the local information (i.e., a portion of a graph instead of the entire graph) during the partitioning. Considering only the local graph information is meaningful because acquiring complete information for large-scale graphs is expensive. Based on the Local Graph Edge Partitioning model, two local graph edge partitioning algorithms—Two-stage Local Partitioning and Adaptive Local Partitioning—are given. Experimental results obtained on 14 real-world graphs demonstrate that the proposed algorithms outperform rival algorithms in most tested cases. Furthermore, the proposed algorithms are proven to significantly improve the efficiency of the real graph computation system GraphX.

scholarly journals Real-world use of key performance indicators for point-of-Care Testing network accredited by ISO 22870

2020 ◽  
Vol 22 ◽  
pp. e00188
Author(s):  
Paloma Oliver ◽  
Pilar Fernandez-Calle ◽  
Roberto Mora ◽  
Jorge Diaz-Garzon ◽  
Daniel Prieto ◽  
...  
Keyword(s):  
Real World ◽  
Performance Indicators ◽  
Point Of Care ◽  
Key Performance Indicators ◽  
Point Of Care Testing

scholarly journals A Two-Stage Offline-to-Online Multiobjective Optimization Strategy for Ship Integrated Energy System Economical/ Environmental Scheduling Problem

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Qing An ◽  
Jun Zhang ◽  
Xin Li ◽  
Xiaobing Mao ◽  
Yulong Feng ◽  
...  
Keyword(s):  
Multiobjective Optimization ◽  
Real World ◽  
Operation Time ◽  
Energy System ◽  
Scheduling Problem ◽  
Storage Space ◽  
Optimization Strategy ◽  
Two Stage ◽  
Integrated Energy System ◽  
And Storage

The economical/environmental scheduling problem (EESP) of the ship integrated energy system (SIES) has high computational complexity, which includes more than one optimization objective, various types of constraints, and frequently fluctuated load demand. Therefore, the intelligent scheduling strategies cannot be applied to the ship energy management system (SEMS) online, which has limited computing power and storage space. Aiming at realizing green computing on SEMS, in this paper a typical SIES-EESP optimization model is built, considering the form of decision vectors, the economical/environmental optimization objectives, and various types of real-world constraints of the SIES. Based on the complexity of SIES-EESPs, a two-stage offline-to-online multiobjective optimization strategy for SIES-EESP is proposed, which transfers part of the energy dispatch online computing task to the offline high-performance computer systems. The specific constraints handling methods are designed to reduce both continuous and discrete constraints violations of SIES-EESPs. Then, an establishment method of energy scheduling scheme-base is proposed. By using the big data offline, the economical/environmental scheduling solutions of a typical year can be obtained and stored with more computing resources and operation time on land. Thereafter, a short-term multiobjective offline-to-online optimization approach by SEMS is considered, with the application of multiobjective evolutionary algorithm (MOEA) and typical schemes corresponding to the actual SIES-EESPs. Simulation results show that the proposed strategy can obtain enough feasible Pareto solutions in a shorter time and get well-distributed Pareto sets with better convergence performance, which can well adapt to the features of real-world SIES-EESPs and save plenty of operation time and storage space for the SEMS.

scholarly journals A simulation approach for aircraft cargo loading considering weight and balance constraints

2021 ◽  
Vol 3 (1) ◽  
pp. 21-31
Author(s):  
Erdem Agbas ◽  
Ali Osman Kusakci
Keyword(s):  
Simulation Model ◽  
Real World ◽  
Performance Indicators ◽  
Center Of Gravity ◽  
Air Cargo ◽  
Unit Load ◽  
Loading Process ◽  
Cargo Transport ◽  
Manual Methods ◽  
The Given

Air cargo transport is a growing industry in parallel with the growth in world trade and e-commerce. The global air cargo transport traffic getting busier, the importance of timely loading with minimum error is increasing. Therefore, digitalization of the air cargo loading process is needed. Assignment of Unit Load Devices (ULDs) to the specific positions on the freighter is performed by loadmasters by manual or semi-manual methods. This study aims to design a simulation model, which performs the ULD assignment automatically by simulating the loading process performed by the experienced loadmasters under the weight and balance constraints. The SEMMA (sample, explore, modify, model, assess) model is used while generating the simulation model. Fifty real-world loading orders were used to assess the performance of the model. The ULD assignment process by the simulation model and the loadmasters using semi-manual loading were compared with regard to time and center of gravity performance indicators. The results demonstrated that the simulation model can load all the given sets of ULDs, as efficiently as a loadmaster with a similar center of gravity in a shorter period of time. In conclusion, the proposed simulation model provides an efficient solution to the ULD assignment problem. However, the base model generated may be improved to address various real-world scenarios

Sound and the City: Current Perspectives on Acoustic Geo-Sensing in Urban Environment

2019 ◽  
Vol 105 (5) ◽  
pp. 766-778 ◽  
Author(s):  
Florian B. Pokorny ◽  
Moritz Fišer ◽  
Franz Graf ◽  
Peter B. Marschik ◽  
Björn W. Schuller
Keyword(s):  
Urban Environment ◽  
Real World ◽  
Cell Phone ◽  
Spatial Information ◽  
Smart Cities ◽  
Sequential Approach ◽  
Real World Applications ◽  
Audio Data ◽  
A Cell ◽  
The City

Acoustic geo-sensing deals with the derivation of spatial information from audio data. Motivated by the rising field of sensing information in (smart) cities, we present current perspectives and a methodological update on the acoustic-based solution of recognition problems in a complex urban real-world scenario. In particular, we examine a static and a sequential approach for the automatic recognition of a cyclist's route between fixed endpoints, the route direction, and the route progress, solely based on the audio data recorded with a cell-phone attached to the cyclist. To this end, we introduce the freely available 'Graz Cell-phone Cycle Corpus extended' (GC3+) that consists of more than 25 h of GPS-annotated audio material recorded in the southern urban area of the city of Graz, Austria. Promising recognition results confirm basic feasibility of acoustic geo-sensing in an urban environment. The approach's theoretical potential of being generalised to support the solution of position tracking problems on a multi-dimensional urban grid gives reason for the implementation of acoustic geo-sensing methodology in a number of real-world applications.

Autonomous Pedestrian Push Button Activation by Outdoor Mobile Robot in Outdoor Environments

2013 ◽  
Vol 25 (3) ◽  
pp. 484-496
Author(s):  
Aneesh N. Chand ◽  
◽  
Shin’ichi Yuta ◽  
Keyword(s):  
Mobile Robot ◽  
Urban Environment ◽  
Real World ◽  
Outdoor Environment ◽  
Push Button ◽  
Outdoor Environments ◽  
Pedestrian Crossing ◽  
Road Crossing ◽  
Unique Ability ◽  
Mechanical Finger

The authors have developed an outdoor mobile robot that has the ability to cross roads at an intersection or pedestrian crossing fully autonomously while traveling along sidewalks in an urban environment. This gives the robot the capability to travel longer and complex routes as the robot is able to cross a road and continue with its path. The developed robot has the unique ability to autonomously approach and activate the pedestrian push button with a mechanical finger. We first briefly describe the overall operation of such a road crossing robot. The rest of this paper then discusses in detail how the robot can meticulously navigate to and activate the pedestrian push button with the on-board finger. The contribution of this work is that although there are robots existing that perform precision docking or button activation, this robot is one of the few that can perform such an action in a real world outdoor environment that is completely unmodified. We prove this by deploying the robot in a real world road-crossing and it was successfully able to engage the pedestrian push button.

LWIR and MWIR fusion algorithm comparison using image metrics

2005 ◽  
Author(s):  
S. K. Chari ◽  
J. D. Fanning ◽  
S. M. Salem ◽  
A. L. Robinson ◽  
C. E. Halford
Keyword(s):  
Fusion Algorithm ◽  
Image Metrics ◽  
Algorithm Comparison

scholarly journals A Two-stage approach for an optimum solution of the car assembly scheduling problem. Part 2. CLP solution and real-world example

2015 ◽  
Vol 25 (3) ◽  
pp. 367-375
Author(s):  
Michał Mazur ◽  
Antoni Niederliński
Keyword(s):  
Logic Programming ◽  
Real World ◽  
Constraint Logic Programming ◽  
Scheduling Problem ◽  
Two Stage ◽  
Assembly Scheduling ◽  
Optimum Solution

Abstract A Constraint Logic Programming (CLP) tool for solving the problem discussed in Part 1 of the paper has been designed. It is outlined and discussed in the paper. The program has been used for solving a real-world car assembly scheduling problem.

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