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One Person Can Supervise a Swarm of 100 Unmanned Autonomous Vehicles

An open research question has been whether a single human can supervise a true heterogeneous swarm of robots completing tasks in real-world environments. A general concern is whether or not the human’s workload will be taxed to the breaking point.

A drone in the hand of one of the OSU researchers involved in the testing for this research. (Image: Karl Maasdam)

Research involving Oregon State University has shown that a “swarm” of more than 100 autonomous ground and aerial robots can be supervised by one person without subjecting the individual to an undue workload.

The findings represent a big step toward efficiently and economically using swarms in a range of roles from wildland firefighting to package delivery to disaster response in urban environments.

“We don’t see a lot of delivery drones yet in the United States, but there are companies that have been deploying them in other countries,” said Julie A. Adams of the OSU College of Engineering. “It makes business sense to deploy delivery drones at a scale, but it will require a single person be responsible for very large numbers of these drones. I’m not saying our work is a final solution that shows everything is OK, but it is the first step toward getting additional data that would facilitate that kind of a system.”

The results, published in Field Robotics, stem from the Defense Advanced Research Project Agency’ program known as OFFSET, short for Offensive Swarm-Enabled Tactics. Adams was part of a group that received an OFFSET grant in 2017.

During the course of the four-year project, researchers deployed swarms of up to 250 autonomous vehicles – multi-rotor aerial drones, and ground rovers – able to gather information in “concrete canyon” urban surroundings where line-of-sight, satellite-based communication is impaired by buildings. The information the swarms collect during their missions at military urban training sites have the potential to help keep U.S. troops and civilians safer.

Adams was a co-principal investigator on one of two swarm system integrator teams that developed the system infrastructure and integrated the work of other teams focused on swarm tactics, swarm autonomy, human-swarm teaming, physical experimentation and virtual environments.

“The project required taking off-the-shelf technologies and building the autonomy needed for them to be deployed by a single human called the swarm commander,” said Adams. “That work also required developing not just the needed systems and the software, but also the user interface for that swarm commander to allow a single human to deploy these ground and aerial systems.”

Collaborators with Smart Information Flow Technologies developed a virtual reality interface called I3 that lets the commander control the swarm with high-level directions.

“The commanders weren’t physically driving each individual vehicle, because if you’re deploying that many vehicles, they can’t – a single human can’t do that,” Adams said. “The idea is that the swarm commander can select a play to be executed and can make minor adjustments to it, like a quarterback would in the NFL. The objective data from the trained swarm commanders demonstrated that a single human can deploy these systems in built environments, which has very broad implications beyond this project.”

Testing took place at multiple Department of Defense Combined Armed Collective Training Facilities. Each multi-day field exercise introduced additional vehicles, and every 10 minutes swarm commanders provided information about their workload and how stressed or fatigued they were.

During the final field exercise, featuring more than 100 vehicles, the commanders’ workload levels were also assessed through physiological sensors that fed information into an algorithm that estimates someone’s sensory channel workload levels and their overall workload.

“The swarm commanders’ workload estimate did cross the overload threshold frequently, but just for a few minutes at a time, and the commander was able to successfully complete the missions, often under challenging temperature and wind conditions,” Adams said.

This work was performed by Julie Adams, Joshua Hamell and Phillip Walker for the Collaborative Robotics and Intelligent Systems Institute, Oregon State University. For more information, download the Technical Support Package (free white paper) below. ADTTSP-04243

Topics:
Aerospace Automation Automation Autonomous vehicles Autonomy Electronics Electronics & Computers Information Technology Robotics Robotics Unmanned Air Vehicles/Systems (UAV/UAS) Vehicles
This Brief includes a Technical Support Package (TSP).
Document cover
Can A Single Human Supervise A Swarm of 100 Heterogeneous Robots?

(reference ADTTSP-04243) is currently available for download from the TSP library.

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    Magazine cover
    Aerospace & Defense Technology Magazine

    This article first appeared in the April, 2024 issue of Aerospace & Defense Technology Magazine (Vol. 9 No. 2).

    Read more articles from this issue here.

    Read more articles from the archives here.

    Overview

    The document presents a study on the supervision of heterogeneous robot swarms, focusing on the capabilities of a single human operator managing a large number of diverse robots in urban environments. This research is part of the DARPA OFFSET (Offensive Swarm-Enabled Tactics) program, which aims to enhance the effectiveness of robotic swarms in military and civilian applications.

    The study highlights the operational dynamics of a swarm consisting of 100 robots, including both Unmanned Ground Vehicles (UGVs) and Unmanned Aerial Vehicles (UAVs). It examines the challenges faced by the human supervisor, particularly in terms of workload management and decision-making under varying conditions. The research utilizes a multidimensional workload algorithm to assess the operator's experience of overload and underload states during the mission.

    Key findings indicate that the overall workload fluctuated between normal and overload states throughout the observation period. For instance, during a specific mission segment, the longest sustained overload period lasted 3 minutes and 35 seconds, while the majority of the time (95% of estimates) was classified as normal workload. This suggests that while the human operator can manage a large number of robots, there are critical moments where the cognitive demands exceed optimal levels.

    The mission plan involved deploying all vehicles at the start of the shift, with the operator issuing multiple tactics that required the robots to autonomously navigate and execute tasks. The study provides insights into the effectiveness of these tactics and the operational challenges posed by vehicle blockages and other environmental factors.

    The document also includes comparative analyses of in situ workload component responses against individual workload estimates, offering a comprehensive view of the operator's performance and the system's responsiveness to changes in workload.

    Overall, the research underscores the potential of human-robot collaboration in complex environments, demonstrating that a single operator can effectively oversee a large swarm of robots, provided that the workload is managed appropriately. The findings contribute to the understanding of human factors in robotic systems and highlight the importance of designing user-friendly interfaces and support systems to enhance operator performance in swarm management.

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