As part of a project to create leader-follower network topologies, a Georgia Tech research team has taught a swarm of small robots to play Beethoven's "Fur Elise" on an electronic keyboard.
A human pianist would play the musical piece by hitting certain keys in different locations at certain times. In a similar way, spatio-temporal requests are delivered to the robots. These requests are a series of spatial locations that must be reached at specified times. The researchers at the Georgia Robotics and Intelligent Systems Laboratory call this application the Robot Music Wall.
The goal of this research, according to the project's website, is "creating application specific leader follower network topologies that are completely controllable." The input (or requests) is sent to the leader node of the network. The rest of the robots operate via a "nearest neighbor averaging" rule. The team says it's developing low-complexity algorithms for such networks.
As part of a project to create leader-follower network topologies, a swarm of Khepera III robots deploys spatio-temporal routing algorithms to use the fewest members and travel the minimum possible distance while playing Beethoven's "Fur Elise." (Source: K-Team)
In this particular exercise, the swarm, in effect, must solve a spatio-temporal routing problem, just as real packet networks do. It must figure out how the fewest possible robots can act as a team to travel the minimum possible distance to play the piece. Using the optimal control strategies developed by the research team, the leader of the robot swarm drives the followers around the wall to play the piece under certain speed, acceleration, and sensor range constraints.
As a one-time player of this lovely piece by the master, I wasn't impressed by the robots' musical abilities. But I was intrigued by their ability to coordinate in space and time. They certainly use less energy as discrete nodes moving in concert than two hands with swarms of five fingers each.
These talented machines are the remote-controlled Khepera III swarm robots made by the Swiss company K-Team. They're a bit larger than I imagined, with a diameter of 130mm (5.1 inches) and a height of 70mm (2.75 inches). But that's probably because they contain a lot of components: a processor, RAM, Flash memory, two DC brushed servo motors, eight infrared (IR) proximity and ambient light sensors, two IR ground proximity sensors, five ultrasonic sensors, communication ports, and a battery pack. With all that, they weigh only 690gm (24.3oz), and their top speed is 0.5m per second. They can be controlled remotely or operate autonomously.
We've written about swarming robots before, especially the talented group from the University of Pennsylvania that danced to light and music at Cannes, as well as the underwater swarm that will help rescue coral reefs. This musical team makes me wonder whether swarming robots could turn dreams into art (like the painting ABB robot) and what that canvas would look like.
Right, if there were at least 3 or 4 times the number of swarm elements (it only starts with 8, after all) or they were that much faster, the ENTIRE piece (the middle section has about 3 times the number of notes in the same period of time) could be played a tempo, and it would be as flawless as if sequenced.
This sort of cooperative solution is intriguing to watch. Could this also be used to deliver multiple parcels throughout a neighborhood with minimal energy consumption? Maybe planting algorithms for reforestation? Battlefield logistics? I'm sure that there must be lots of real-world problems that could use this sort of optimization for a solution.
Thanks, mrdon, glad you liked it. I was happy to find out that the U of PA robot musical team we've written about wasn't the only group of swarming bots with such talents. I suggest you check out the link we gave for the Kephera IIIs--they are OTS machines, as Cabe points out. I think his point about the software is also well taken. I'd like to know more about what the Georgia Tech team did with spatio-temporal request sequencing.
A completely different concept, that is true. As for the working together, what came to my mind is the expression "Gung Ho", adopted by the USMC many years ago. The meaning, loosely translated from the original Chinese, means "work together". And the robots certainly do. It ia a little bit like watching an untrianed typist using whatever finger is closest to the needed key.
Is it possible that these robots could learn to type? That would be quite a show, no doubt.
Robots that walk have come a long way from simple barebones walking machines or pairs of legs without an upper body and head. Much of the research these days focuses on making more humanoid robots. But they are not all created equal.
The IEEE Computer Society has named the top 10 trends for 2014. You can expect the convergence of cloud computing and mobile devices, advances in health care data and devices, as well as privacy issues in social media to make the headlines. And 3D printing came out of nowhere to make a big splash.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.