971 research outputs found
Arctic Domain Awareness Center DHS Center of Excellence (COE): Project Work Plan
As stated by the DHS Science &Technology Directorate, “The increased and diversified use of maritime
spaces in the Arctic - including oil and gas exploration, commercial activities, mineral speculation, and
recreational activities (tourism) - is generating new challenges and risks for the U.S. Coast Guard and
other DHS maritime missions.” Therefore, DHS will look towards the new ADAC for research to
identify better ways to create transparency in the maritime domain along coastal regions and inland
waterways, while integrating information and intelligence among stakeholders. DHS expects the ADAC
to develop new ideas to address these challenges, provide a scientific basis, and develop new approaches
for U.S. Coast Guard and other DHS maritime missions. ADAC will also contribute towards the
education of both university students and mid-career professionals engaged in maritime security.
The US is an Arctic nation, and the Arctic environment is dynamic. We have less multi-year ice and more
open water during the summer causing coastal villages to experience unprecedented storm surges and
coastal erosion. Decreasing sea ice is also driving expanded oil exploration, bringing risks of oil spills.
Tourism is growing rapidly, and our fishing fleet and commercial shipping activities are increasing as
well. There continues to be anticipation of an economic pressure to open up a robust northwest passage
for commercial shipping. To add to the stresses of these changes is the fact that these many varied
activities are spread over an immense area with little connecting infrastructure. The related maritime
security issues are many, and solutions demand increasing maritime situational awareness and improved
crisis response capabilities, which are the focuses of our Work Plan.
UAA understands the needs and concerns of the Arctic community. It is situated on Alaska’s Southcentral
coast with the port facility through which 90% of goods for Alaska arrive. It is one of nineteen US
National Strategic Seaports for the US DOD, and its airport is among the top five in the world for cargo
throughput.
However, maritime security is a national concern and although our focus is on the Arctic environment, we
will expand our scope to include other areas in the Lower 48 states. In particular, we will develop sensor
systems, decision support tools, ice and oil spill models that include oil in ice, and educational programs
that are applicable to the Arctic as well as to the Great Lakes and Northeast.
The planned work as detailed in this document addresses the DHS mission as detailed in the National
Strategy for Maritime Security, in particular, the mission to Maximize Domain Awareness (pages 16 and
17.) This COE will produce systems to aid in accomplishing two of the objectives of this mission. They
are: 1) Sensor Technology developing sensor packages for airborne, underwater, shore-based, and
offshore platforms, and 2) Automated fusion and real-time simulation and modeling systems for decision
support and planning. An integral part of our efforts will be to develop new methods for sharing of data
between platforms, sensors, people, and communities.United States Department of Homeland SecurityCOE ADAC Objective/Purpose / Methodology / Center Management Team and Partners / Evaluation and Transition Plans / USCG Stakeholder Engagement / Workforce Development Strategy / Individual Work Plan by Projects Within a Theme / Appendix A / Appendix B / Appendix
Communication and Control in Collaborative UAVs: Recent Advances and Future Trends
The recent progress in unmanned aerial vehicles (UAV) technology has
significantly advanced UAV-based applications for military, civil, and
commercial domains. Nevertheless, the challenges of establishing high-speed
communication links, flexible control strategies, and developing efficient
collaborative decision-making algorithms for a swarm of UAVs limit their
autonomy, robustness, and reliability. Thus, a growing focus has been witnessed
on collaborative communication to allow a swarm of UAVs to coordinate and
communicate autonomously for the cooperative completion of tasks in a short
time with improved efficiency and reliability. This work presents a
comprehensive review of collaborative communication in a multi-UAV system. We
thoroughly discuss the characteristics of intelligent UAVs and their
communication and control requirements for autonomous collaboration and
coordination. Moreover, we review various UAV collaboration tasks, summarize
the applications of UAV swarm networks for dense urban environments and present
the use case scenarios to highlight the current developments of UAV-based
applications in various domains. Finally, we identify several exciting future
research direction that needs attention for advancing the research in
collaborative UAVs
Collaborative Multi-Robot Search and Rescue: Planning, Coordination, Perception, and Active Vision
Search and rescue (SAR) operations can take significant advantage from supporting autonomous or teleoperated robots and multi-robot systems. These can aid in mapping and situational assessment, monitoring and surveillance, establishing communication networks, or searching for victims. This paper provides a review of multi-robot systems supporting SAR operations, with system-level considerations and focusing on the algorithmic perspectives for multi-robot coordination and perception. This is, to the best of our knowledge, the first survey paper to cover (i) heterogeneous SAR robots in different environments, (ii) active perception in multi-robot systems, while (iii) giving two complementary points of view from the multi-agent perception and control perspectives. We also discuss the most significant open research questions: shared autonomy, sim-to-real transferability of existing methods, awareness of victims' conditions, coordination and interoperability in heterogeneous multi-robot systems, and active perception. The different topics in the survey are put in the context of the different challenges and constraints that various types of robots (ground, aerial, surface, or underwater) encounter in different SAR environments (maritime, urban, wilderness, or other post-disaster scenarios). The objective of this survey is to serve as an entry point to the various aspects of multi-robot SAR systems to researchers in both the machine learning and control fields by giving a global overview of the main approaches being taken in the SAR robotics area
Using Unmanned Aerial Vehicles for Wireless Localization in Search and Rescue
This thesis presents how unmanned aerial vehicles (UAVs) can successfully assist in search and rescue (SAR) operations using wireless localization. The zone-grid to partition to capture/detect WiFi probe requests follows the concepts found in Search Theory Method. The UAV has attached a sensor, e.g., WiFi sniffer, to capture/detect the WiFi probes from victims or lost people’s smartphones. Applying the Random-Forest based machine learning algorithm, an estimation of the user\u27s location is determined with a 81.8% accuracy.
UAV technology has shown limitations in the navigational performance and limited flight time. Procedures to optimize these limitations are presented. Additionally, how the UAV is maneuvered during flight is analyzed, considering different SAR flight patterns and Li-Po battery consumption rates of the UAV. Results show that controlling the UAV by remote-controll detected the most probes, but it is less power efficient compared to control it autonomously
Edge Artificial Intelligence for Real-Time Target Monitoring
The key enabling technology for the exponentially growing cellular communications sector is location-based services. The need for location-aware services has increased along with the number of wireless and mobile devices. Estimation problems, and particularly parameter estimation, have drawn a lot of interest because of its relevance and engineers' ongoing need for higher performance. As applications expanded, a lot of interest was generated in the accurate assessment of temporal and spatial properties.
In the thesis, two different approaches to subject monitoring are thoroughly addressed. For military applications, medical tracking, industrial workers, and providing location-based services to the mobile user community, which is always growing, this kind of activity is crucial.
In-depth consideration is given to the viability of applying the Angle of Arrival (AoA) and Receiver Signal Strength Indication (RSSI) localization algorithms in real-world situations. We presented two prospective systems, discussed them, and presented specific assessments and tests. These systems were put to the test in diverse contexts (e.g., indoor, outdoor, in water...). The findings showed the localization capability, but because of the low-cost antenna we employed, this method is only practical up to a distance of roughly 150 meters. Consequently, depending on the use-case, this method may or may not be advantageous. An estimation algorithm that enhances the performance of the AoA technique was implemented on an edge device.
Another approach was also considered. Radar sensors have shown to be durable in inclement weather and bad lighting conditions. Frequency Modulated Continuous Wave (FMCW) radars are the most frequently employed among the several sorts of radar technologies for these kinds of applications. Actually, this is because they are low-cost and can simultaneously provide range and Doppler data. In comparison to pulse and Ultra Wide Band (UWB) radar sensors, they also need a lower sample rate and a lower peak to average ratio. The system employs a cutting-edge surveillance method based on widely available FMCW radar technology. The data processing approach is built on an ad hoc-chain of different blocks that transforms data, extract features, and make a classification decision before cancelling clutters and leakage using a frame subtraction technique, applying DL algorithms to Range-Doppler (RD) maps, and adding a peak to cluster assignment step before tracking targets. In conclusion, the FMCW radar and DL technique for the RD maps performed well together for indoor use-cases. The aforementioned tests used an edge device and Infineon Technologies' Position2Go FMCW radar tool-set
A Survey on UAV-Aided Maritime Communications: Deployment Considerations, Applications, and Future Challenges
Maritime activities represent a major domain of economic growth with several
emerging maritime Internet of Things use cases, such as smart ports, autonomous
navigation, and ocean monitoring systems. The major enabler for this exciting
ecosystem is the provision of broadband, low-delay, and reliable wireless
coverage to the ever-increasing number of vessels, buoys, platforms, sensors,
and actuators. Towards this end, the integration of unmanned aerial vehicles
(UAVs) in maritime communications introduces an aerial dimension to wireless
connectivity going above and beyond current deployments, which are mainly
relying on shore-based base stations with limited coverage and satellite links
with high latency. Considering the potential of UAV-aided wireless
communications, this survey presents the state-of-the-art in UAV-aided maritime
communications, which, in general, are based on both conventional optimization
and machine-learning-aided approaches. More specifically, relevant UAV-based
network architectures are discussed together with the role of their building
blocks. Then, physical-layer, resource management, and cloud/edge computing and
caching UAV-aided solutions in maritime environments are discussed and grouped
based on their performance targets. Moreover, as UAVs are characterized by
flexible deployment with high re-positioning capabilities, studies on UAV
trajectory optimization for maritime applications are thoroughly discussed. In
addition, aiming at shedding light on the current status of real-world
deployments, experimental studies on UAV-aided maritime communications are
presented and implementation details are given. Finally, several important open
issues in the area of UAV-aided maritime communications are given, related to
the integration of sixth generation (6G) advancements
An overview of robotics and autonomous systems for harsh environments
Across a wide range of industries and applications, robotics and autonomous systems can fulfil the crucial and challenging tasks such as inspection, exploration, monitoring, drilling, sampling and mapping in areas of scientific discovery, disaster prevention, human rescue and infrastructure management, etc. However, in many situations, the associated environment is either too dangerous or inaccessible to humans. Hence, a wide range of robots have been developed and deployed to replace or aid humans in these activities. A look at these harsh environment applications of robotics demonstrate the diversity of technologies developed. This paper reviews some key application areas of robotics that involve interactions with harsh environments (such as search and rescue, space exploration, and deep-sea operations), gives an overview of the developed technologies and provides a discussion of the key trends and future directions common to many of these areas
Supporting UAVs with Edge Computing: A Review of Opportunities and Challenges
Over the last years, Unmanned Aerial Vehicles (UAVs) have seen significant
advancements in sensor capabilities and computational abilities, allowing for
efficient autonomous navigation and visual tracking applications. However, the
demand for computationally complex tasks has increased faster than advances in
battery technology. This opens up possibilities for improvements using edge
computing. In edge computing, edge servers can achieve lower latency responses
compared to traditional cloud servers through strategic geographic deployments.
Furthermore, these servers can maintain superior computational performance
compared to UAVs, as they are not limited by battery constraints. Combining
these technologies by aiding UAVs with edge servers, research finds measurable
improvements in task completion speed, energy efficiency, and reliability
across multiple applications and industries. This systematic literature review
aims to analyze the current state of research and collect, select, and extract
the key areas where UAV activities can be supported and improved through edge
computing
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