Dynamically Weighted Factor-Graph for Feature-based Geo-localization

Feature-based geo-localization relies on associating features extracted from aerial imagery with those detected by the vehicle's sensors. This requires that the type of landmarks must be observable from both sources. This no-variety of feature types generates poor representations that lead to outliers and deviations, produced by ambiguities and lack of detections respectively. To mitigate these drawbacks, in this paper, we present a dynamically weighted factor graph model for the vehicle's trajectory estimation. The weight adjustment in this implementation depends on information quantification in the detections performed using a LiDAR sensor. Also, a prior (GNSS-based) error estimation is included in the model. Then, when the representation becomes ambiguous or sparse, the weights are dynamically adjusted to rely on the corrected prior trajectory, mitigating in this way outliers and deviations. We compare our method against state-of-the-art geo-localization ones in a challenging ambiguous environment, where we also cause detection losses. We demonstrate mitigation of the mentioned drawbacks where the other methods fail.Comment: This paper is under review at the journal "IEEE Robotics and Automation Letters

Geo-Localization Based on Dynamically Weighted Factor-Graph

Feature-based geo-localization relies on associating features extracted from aerial imagery with those detected by the vehicle's sensors. This requires that the type of landmarks must be observable from both sources. This lack of variety of feature types generates poor representations that lead to outliers and deviations produced by ambiguities and lack of detections, respectively. To mitigate these drawbacks, in this letter, we present a dynamically weighted factor graph model for the vehicle's trajectory estimation. The weight adjustment in this implementation depends on information quantification in the detections performed using a LiDAR sensor. Also, a prior (GNSS-based) error estimation is included in the model. Then, when the representation becomes ambiguous or sparse, the weights are dynamically adjusted to rely on the corrected prior trajectory, mitigating outliers and deviations in this way. We compare our method against state-of-the-art geo-localization ones in a challenging and ambiguous environment, where we also cause detection losses. We demonstrate mitigation of the mentioned drawbacks where the other methods fail.This work was supported in part by Regional Valencian Community Government and the European Union under Project PROMETEO/2021/075 and in part by Spanish Government under Grant PRE2019-088069, Grant PRE2022-101680, and Project PID2021-122685OB-I00

Data validation and quality assessment of voluntary geographic information road network of Castellon for emergency route planning

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesDisasters are unpredictable. Natural disasters such as earthquake, flood, landslide or man-made disaster such as fire, road accident can affect our life anytime. Many casualties occur during the disaster on the absence of preparedness and prevention measure. Lack of evacuation routes and the timely response to the injured people to the nearby emergency services is one of the main sources for a large number of casualties. Proper response operations must be carried out, as a slight delay can risk the lives of citizens. Since disaster cannot be mitigated, preventive measures before and after the disaster are important. Spatial data play a significant role in emergency management: preparedness, response, recovery, and mitigation. A suitable network analysis aids to a smooth network and especially helps during a disaster. In this paper, Castellon network dataset is developed using validated Voluntary Geographic Information. It is developed to find the fastest route to the emergency services, especially during or after the occurrence of a disaster. Data quality assurance is performed using positional, attribute and network length check to produce efficient results. The fastest and safest route to and from the emergency services are recognized to plan safety measure during the occurrence of a disaster. The evaluation of the network by participants provides insight into the quality and use of the network in a disaster scenario. It also reveals that VGI can be used further in the preparation of a disaster prevention system for various cities

Morphology of travel routes and the organization of cities

This is the final version. Available from Nature Research via the DOI in this recordData availability. All data needed to evaluate the conclusions are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors and are also available at https://github.com/mlee96/inness_research.The city is a complex system that evolves through its inherent social and economic interactions. Mediating the movements of people and resources, urban street networks offer a spatial footprint of these activities. Of particular interest is the interplay between street structure and its functional usage. Here, we study the shape of 472,040 spatiotemporally optimized travel routes in the 92 most populated cities in the world, finding that their collective morphology exhibits a directional bias influenced by the attractive (or repulsive) forces resulting from congestion, accessibility, and travel demand. To capture this, we develop a simple geometric measure, inness, that maps this force field. In particular, cities with common inness patterns cluster together in groups that are correlated with their putative stage of urban development as measured by a series of socio-economic and infrastructural indicators, suggesting a strong connection between urban development, increasing physical connectivity, and diversity of road hierarchies.US Army Research OfficeNational Research Foundation of Korea funded by the Ministry of Science and ICTMinistry of Education of the Republic of Kore

Wearable Urban Mobility Assistive Device for Visually Impaired Pedestrians Using a Smartphone and a Tactile-Foot Interface

This paper reports on the progress of a wearable assistive technology (AT) device designed to enhance the independent, safe, and efficient mobility of blind and visually impaired pedestrians in outdoor environments. Such device exploits the smartphone’s positioning and computing capabilities to locate and guide users along urban settings. The necessary navigation instructions to reach a destination are encoded as vibrating patterns which are conveyed to the user via a foot-placed tactile interface. To determine the performance of the proposed AT device, two user experiments were conducted. The first one requested a group of 20 voluntary normally sighted subjects to recognize the feedback provided by the tactile-foot interface. The results showed recognition rates over 93%. The second experiment involved two blind voluntary subjects which were assisted to find target destinations along public urban pathways. Results show that the subjects successfully accomplished the task and suggest that blind and visually impaired pedes-trians might find the AT device and its concept approach useful, friendly, fast to master, and easy to use