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Defense & Security

3D-printed rapid disaster response

3D-printed robots are easily adapted to specific tasks and payloads and can be quickly dispatched in emergency situations.
25 April 2014, SPIE Newsroom. DOI: 10.1117/2.1201404.005459

The US Department of Homeland Security (DHS) is increasingly using robots in military operations and in response to domestic emergencies. However, selecting and prepositioning the appropriate robotic assets can be difficult, because of the prohibitive cost. Furthermore, there are specific requirements for task-appropriate attachments, the correct track or wheels for the terrain, the size or weight of the platform, and the sensor-carrying capability.

Purchase SPIE Field Guide to IR Systems, Detectors and FPAsAdditive manufacturing and 3D printing enable quick, efficient, and cost-effective production of critical items for immediate use in emergency situations. Robotic Research, sponsored by DHS Science and Technology, is developing an affordable and adaptable system1 that uses 3D printing to produce robots and other specialized devices during disaster response. The system contains a library of robots: a storefront for designs, interactive elements, a database, and a complete workflow for keeping track of the information needed, from model design to operation of the printed equipment. There are currently multiple robots and device designs, with more being developed, and we are building compatible libraries for commercial and government use. These would allow third-party developers to maintain their intellectual property and receive payment if their devices are realized.

Not all robot components can be 3D printed: motors and sensors being examples that cannot. DHS specifies a common set of these non-printed parts that all the robot designs use. If a hundred robots require a small motor, they all use the same model, rather than a hundred different motors. This approach reduces the required inventory of non-printed parts.

We designed an initial set of platforms for DHS for proof of concept. The Throwable Orientation Switching Robot (TOSR) is a small, throwable, two-wheeled remote-controlled robot (see Figure 1). TOSR's body is 3D printed in acrylonitrile butadiene styrene and its wheels are a combination of stiff and flexible materials to help the robot survive being thrown. TOSR currently carries a camera payload with LED lighting and transmits the video wirelessly to an operator control unit. The camera is positioned to see in front of the robot when driving, but can tilt upward to inspect objects above. The system is particularly useful in situations where recovery of the platform may not be possible (e.g., chemical or biological survey, or a building collapse). Because we print TOSR from scratch, we can easily adapt it to carry additional payloads as required, and thus it provides an easy-to-use, adaptable, low-cost robotic platform. We tested the robot at the Naval Postgraduate School's field program in February 2014, where we threw and drove it in a variety of terrains.


Figure 1. The Throwable Orientation Switching Robot, comprising 3D-printed body and wheels.

Another platform, the Remote Aerial Payload Transport Robot (RAPTR), is a 3D-printed aerial hexarotor platform (see Figure 2). RAPTR is capable of carrying a small hemorrhage/trauma kit and incorporates a camera to provide remote feedback to the operator. Using the operator control unit, it is possible to have RAPTR autonomously fly a specified set of waypoints (markers). Like TOSR, its 3D-printed fabrication means the model can be easily adapted to new mission needs, such as additional payloads.

In the future, rapid manufacturing will solve a variety of complex problems by offering customization, low cost, just-in-time availability, and rapid modification for individual tasks. Therefore, the problem now is not a lack of models but how to sort, share, and find these models and match them to specific needs.


Figure 2. The Remote Aerial Payload Transport Robot, capable of carrying a small trauma kit and camera.

We are working with the Army Rapid Equipping Force to develop the interface for a library of 3D-printable systems, the Expeditionary Additive Module, which would allow operators to search the collection of robots to be built. The system would provide instructions to print and assemble the selected robot, and tutorials for training and use. Our work currently focuses on disaster response, but we plan to extend it to a range of customers, including domestic law enforcement, armed services, universities, and research facilities.


Alberto Lacaze, Karl Murphy, Edward Mottern, Katrina Corley
Robotic Research, LLC
Gaithersburg, MD

Alberto Lacaze is president and cofounder of Robotic Research, LLC, and has extensive experience with software, sensors, and techniques to support unmanned autonomous mobility for ground vehicles. He holds an MS in electrical engineering from Drexel University and a BS in electrical engineering and in computer engineering, from Florida Institute of Technology.

Karl Murphy is vice president and cofounder of Robotic Research, LLC, and has extensive experience developing navigation and control systems for autonomous vehicles, terrain perception using lidar and other sensors, and maritime unmanned systems applications. He holds an MS in mechanical engineering from Carnegie Mellon University and a BS in mechanical engineering from Virginia Polytechnic Institute and State University.

Edward Mottern has more than 12 years of program management, robotic vehicle development, integration, and testing experience with major Department of Defense unmanned systems programs. He holds an MS in systems engineering from John Hopkins University (2010) and a BS in electrical engineering/BS in computer engineering from West Virginia University (2002).

Katrina Corley has extensive experience in computer-aided design, robotic systems testing and integration, and additive manufacturing processes. She holds an MS in mechanical engineering with a robotics focus from Embry-Riddle Aeronautical University in Daytona Beach (2011) and a BS in mechanical engineering from Georgia Institute of Technology in Atlanta (2009).


References:
1. A. Lacaze, K. Murphy, E. Mottern, K. Corley, 3D printed rapid disaster response, Proc. SPIE 9118, 2014. Paper accepted at SPIE Indep. Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosyst., Nanoeng. XII Conf. in Baltimore, MD, 7–9 May 2014.