Last fall, two quarter-scale Piper Cub aircraft (two UAVs) and a Porsche Cayenne operated without any humans at the controls on an army robotics rodeo. Each robot had an onboard computer running collaborative software that transformed the three machines into an autonomous, interoperable system.
Back in 2000, the U.S. Department of Defense (DOD) had fewer than 50 UAVs in its inventory; by early 2010, it had more than 7000. None of these systems are fully autonomous.
Unmanned systems still fall short in three key areas: sensing, testing, and interoperability.
A swarm of small robots scatters across the floor of an abandoned warehouse. Each tread-wheeled bot, looking like a tiny tank with a mastlike antenna sticking out of its top, investigates the floor space around it using a video camera to identify windows and doors and a laser scanner to measure distances. Employing a technique called SLAM (for “simultaneous localization and mapping”), it creates a map of its surroundings, keeping track of its own position within the map. When it meets up with another robot, the two exchange maps and then head off to explore uncharted territory, eventually creating a detailed map of the entire floor.
These ingenious mapping robots, designed by researchers through the U.S. Army–funded Micro Autonomous Systems and Technology program, represent the cutting edge of robot autonomy. In future iterations, their designers plan to equip the machines with wall-penetrating radar and infrared sensors, as well as a flexible “whisker” to sense proximity to obstacles. Clever as they are, though, these robots lack a key capability that all future robots will need: They cannot easily interact with other kinds of robots.
Now consider the U.S. Navy’s Littoral Combat Ship. Rather than having a fixed architecture, it will have swappable “mission modules” that include vertical takeoff unmanned aerial vehicles, unmanned underwater vehicles, and unmanned surface vehicles. All these robotic systems will have to operate in concert with each other as well as with manned systems, to support intelligence, surveillance, and reconnaissance missions, oceanographic surveys, mine warfare, port security, and so on.
A particular difficulty is that most automation and control approaches, especially those used for collaborating, assume that all the unmanned systems have the same level of autonomy and the same software architecture. In practice, that is almost never the case, unless the robots have been designed from scratch to work together. Clearly, new approaches are needed so that you can introduce an unknown, autonomous system without having to reconfigure the entire suite of robots.
Interoperability between manned and unmanned systems is even more challenging. Robots will need to understand human language and intent, and they will need to learn to communicate in a way that is natural for humans.
When a UAV needs to communicate with an unmanned ground vehicle, should it use JAUS or STANAG-4586 or something else entirely? The most promising effort in this arena is the JAUS Tool Set, an open, standards-based unmanned vehicle messaging suite that is in beta testing. Using the tool set seems to improve interactions among unmanned vehicles. In the future, the tool set should allow the two message formats to be merged. Ultimately, that should accelerate the deployment of compatible and interoperable unmanned systems.
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
Known for identifying cutting edge technologies, he is currently a Co-Founder of a startup and fundraiser for high potential early-stage companies. He is the Head of Research for Allocations for deep technology investments and an Angel Investor at Space Angels.
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