The Joint Research Project Ankommen – Exploration Using Automated Uav and Ugv

Alamouri, Ahmed; Gerke, M.; Batzdorfer, Simon; Becker, Martin; Bestmann, Ulf; Bobbe, Markus; Khedar, Yogesh; Blume, Thorsten; Schattenberg, Jan; Schmiemann, J.

doi:10.5194/isprs-archives-xlii-2-w13-165-2019

Cited by 5 publications

(3 citation statements)

References 7 publications

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“…Other works address this problem, but assume GPS availability for relative localization. The ANKommEn project [4], [17] uses UAVs and UGVs to build multi-modal maps. GPS is used as the primary means of localization, though the authors perform map alignment for further refinement as a post-processing step.…”

Section: A Collaborationmentioning

confidence: 99%

“…In particular, heterogeneous systems can take advantage of the specific strengths of different robots in the team to complete a task more effectively compared to homogeneous unspecialized teams [2]. Most terrestrial mobile robots are either unmanned ground vehicles (UGVs) or aerial vehicles (UAVs), and so a number of works have investigated synergies between these two groups [3], [4], [5].…”

Section: Introductionmentioning

confidence: 99%

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Stronger Together: Air-Ground Robotic Collaboration Using Semantics

Miller¹,

Cladera²,

Smith³

et al. 2022

Preprint

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In this work, we present an end-to-end heterogeneous multi-robot system framework where ground robots are able to localize, plan, and navigate in a semantic map created in real time by a high-altitude quadrotor. The ground robots choose and deconflict their targets independently, without any external intervention. Moreover, they perform cross-view localization by matching their local maps with the overhead map using semantics. The communication backbone is opportunistic and distributed, allowing the entire system to operate with no external infrastructure aside from GPS for the quadrotor. We extensively tested our system by performing different missions on top of our framework over multiple experiments in different environments. Our ground robots travelled over 6 km autonomously with minimal intervention in the real world and over 96 km in simulation without interventions.

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Section: A Collaborationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Stronger Together: Air-Ground Robotic Collaboration Using Semantics

Miller¹,

Cladera²,

Smith³

et al. 2022

Preprint

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show abstract

“…UAVs have proven to be an important instrument for various disaster scenarios (Alamouri et al, 2019;Erdelj et al, 2017). Unlike traditional geodata acquisitions techniques, such as aerial photogrammetry or satellite surveys, UAVs feature a considerably more agile operational readiness allowing for immediate on-site data capture, processing and visualisation which ultimately expedites decision-making support for first responders.…”

Section: Introductionmentioning

confidence: 99%

A Versatile Uav Near Real-Time Mapping Solution for Disaster Response – Concept, Ideas and Implementation

Fanta-Jende

Steininger

Bruckmüller

et al. 2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. In recent years, the proliferation and further development of unmanned aerial vehicles (UAVs) led to a great number of key technologies, advances and opportunities especially in the realm of time-critical applications. UAVs as a platform provide a unique combination of flexibility, affordability and sensor technology which enables the design of cost-effective and intriguing services particularly for disaster response. This contribution presents a concept for UAV-based near real-time mapping system for disaster relief to provide decision-making support for first responders particularly for possible disaster scenarios in Austria. We outline our system concept and its respective architecture, discuss requirements from a stakeholder perspective as well as legal regulations and initiatives at an EU level. In the methodology section of this paper, the preliminary data processing pipeline with respect to the near real-time orthomosaic generation and the semantic segmentation network are presented. Lastly, first experimental results of the pipeline are shown, and further advances are discussed.

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Development of a methodology for real-time retrieving and viewing of spatial data in emergency scenarios

Alamouri

Hassan²,

Gerke

2021

Appl Geomat

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Quick response in emergency situations is crucial, because any delay can result in dramatic consequences and potentially human losses. Therefore, many institutions/authorities are relying on development of strategies for emergency management, specially to have a quick response process using modern technologies like unmanned aerial vehicles. A key factor affecting this process is to have a quick geo-situation report of the emergency in real time, which reflects the current emergency situation and supports in right decision-making. Providing such geo-reports is still not an easy task because—in most cases—a priori known spatial data like map data (raster/vector) or geodatabases are outdated, and anyway would not provide an overview on the current situation. Therefore, this paper introduces a management methodology of spatial data focusing on enabling a free access and viewing the data of interest in real time and in situ to support emergency managers. The results of this work are twofold: on the one hand, an automated mechanism for spatial data synchronization and streaming was developed and on the other hand, a spatial data sharing concept was realized using web map tile service. For results assessment, an experimental framework through the joint research project ANKommEn (English acronym: Automated Navigation and Communication for Exploration) was implemented. The assessment procedure was achieved based on specific evaluation criteria like time consumption and performance and showed that the developed methodology can help in overcoming some of existing challenges and addressing the practically relevant questions concerning on the complexity in spatial data sharing and retrieval.

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The Joint Research Project Ankommen – Exploration Using Automated Uav and Ugv

Cited by 5 publications

References 7 publications

Stronger Together: Air-Ground Robotic Collaboration Using Semantics

Stronger Together: Air-Ground Robotic Collaboration Using Semantics

A Versatile Uav Near Real-Time Mapping Solution for Disaster Response – Concept, Ideas and Implementation

Development of a methodology for real-time retrieving and viewing of spatial data in emergency scenarios

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