skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Attention:

The NSF Public Access Repository (PAR) system and access will be unavailable from 10:00 PM to 12:00 PM ET on Tuesday, March 25 due to maintenance. We apologize for the inconvenience.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Area-Optimized UAV Swarm Network for Search and Rescue Operations
Intelligent robot swarms are increasingly being explored as tools for search and rescue missions. Efficient path planning and robust communication networks are critical elements of completing missions. The focus of this research is to give unmanned aerial vehicles (UAVs) the ability to self-organize a mesh network that is optimized for area coverage. The UAVs will be able to read the communication strength between themselves and all the UAVs it is connected to using RSSI. The UAVs should be able to adjust their positioning closer to other UAVs if RSSI is below a threshold, and they should also maintain communication as a group if they move together along a search path. Our approach was to use Genetic Algorithms in a simulated environment to achieve multi-node exploration with emphasis on connectivity and swarm spread.  more » « less
Award ID(s):
1757929
PAR ID:
10211199
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
Computing and Communication Workshop and Conference (CCWC)
Page Range / eLocation ID:
0613 to 0618
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; (, Model-Driven Requirements Engineering)
    null (Ed.)
    The use of semi-autonomous Unmanned Aerial Vehicles (UAVs or drones) to support emergency response scenarios, such as fire surveillance and search-and-rescue, has the potential for huge societal benefits. Onboard sensors and artificial intelligence (AI) allow these UAVs to operate autonomously in the environment. However, human intelligence and domain expertise are crucial in planning and guiding UAVs to accomplish the mission. Therefore, humans and multiple UAVs need to collaborate as a team to conduct a time-critical mission successfully. We propose a meta-model to describe interactions among the human operators and the autonomous swarm of UAVs. The meta-model also provides a language to describe the roles of UAVs and humans and the autonomous decisions. We complement the meta-model with a template of requirements elicitation questions to derive models for specific missions. We also identify common scenarios where humans should collaborate with UAVs to augment the autonomy of the UAVs. We introduce the meta-model and the requirements elicitation process with examples drawn from a search-and-rescue mission in which multiple UAVs collaborate with humans to respond to the emergency. We then apply it to a second scenario in which UAVs support first responders in fighting a structural fire. Our results show that the meta-model and the template of questions support the modeling of the human-on-the-loop human interactions for these complex missions, suggesting that it is a useful tool for modeling the human-on-the-loop interactions for multi-UAVs missions. 
    more » « less
  2. ; ; ; (, Proceedings - International Conference on Computer Communications and Networks)
    Efficient path planning and communication of multi-robot systems in the case of a search and rescue operation is a critical issue facing robotics disaster relief efforts. Ensuring all the nodes of a specialized robotic search team are within range, while also covering as much area as possible to guarantee efficient response time, is the goal of this paper. We propose a specialized search-and-rescue model based on a mesh network topology of aerial and ground robots. The proposed model is based on several methods. First, each robot determines its position relative to other robots within the system, using RSSI. Packets are then communicated to other robots in the system detailing important information regarding robot system status, status of the mission, and identification number. The results demonstrate the ability to determine multi-robot navigation with RSSI, allowing low computation costs and increased search-and-rescue time efficiency. 
    more » « less
  3. ; ; ; ; ; (, Software Product Line Conference)
    null (Ed.)
    Unmanned Aerial Vehicles (UAVs) are increasingly used by emergency responders to support search-and-rescue operations, medical supplies delivery, fire surveillance, and many other scenarios. At the same time, researchers are investigating usage scenarios in which UAVs are imbued with a greater level of autonomy to provide automated search, surveillance, and delivery capabilities that far exceed current adoption practices. To address this emergent opportunity, we are developing a configurable, multi-user, multi-UAV system for supporting the use of semi-autonomous UAVs in diverse emergency response missions. We present a requirements-driven approach for creating a software product line (SPL) of highly configurable scenarios based on different missions. We focus on the process for eliciting and modeling a family of related use cases, constructing individual feature models, and activity diagrams for each scenario, and then merging them into an SPL. We show how the SPL will be implemented through leveraging and augmenting existing features in our DroneResponse system. We further present a configuration tool, and demonstrate its ability to generate mission-specific configurations for 20 different use case scenarios. 
    more » « less
  4. (, Proceedings of the International ISCRAM Conference)
    Robots such as unmanned aerial vehicles (UAVs) deployed for search and rescue (SAR) can explore areas where human searchers cannot easily go and gather information on scales that can transform SAR strategy. Multi-UAV teams therefore have the potential to transform SAR by augmenting the capabilities of human teams and providing information that would otherwise be inaccessible. Our research aims to develop new theory and technologies for field deploying autonomous UAVs and managing multi-UAV teams working in concert with multi-human teams for SAR. Specifically, in this paper we summarize our work in progress towards these goals, including: (1) a multi-UAV search path planner that adapts to human behavior; (2) an in-field distributed computing prototype that supports multi-UAV computation and communication; (3) behavioral modeling that fields spatially localized predictions of lost person location; and (4) an interface between human searchers and UAVs that facilitates human-UAV interaction over a wide range of autonomy. 
    more » « less
  5. ; ; (, IEEE)
    In an indoor space, determining a person's mobility patterns has research significance and applicability in real-world scenarios. When mobility patterns are determined, layout optimization can be implemented in indoor spaces to improve efficiency. This research aimed to determine a person's path using Received Signal Strength Indicator (RSSI) data collected from Bluetooth-enabled mobile devices. Mobile app-based mobility detection using Bluetooth RSSI has the advantage of low cost and easy implementation. The research methodology involves developing a Bluetooth RSSI mobility application system to determine the path of a moving mobile device using a vectorized algorithm. The paper presents challenges in creating such a software system, its architecture, the data collection and analysis process, and the results of mobility detection. This research shows that Bluetooth-enabled mobile devices and Bluetooth RSSI data can be used to determine the path in an indoor space with workable accuracy. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email