The End

I Finished My M.Sc. So this blog lost it´s purpose. I´m now at COPPE - UFRJ pursuing my PhD, this time focused in NIALM methods, motivated mainly by energy efficiency. Soon I will create a new blog on the topic.

Warehouse Robots Get Smarter With Ant Intelligence

Amazon may have just gotten its claws into Kiva Systems, but there's more than one company out there looking to automate warehouses with smart little robots. At the Fraunhofer Institute for Material Flow and Logistics, researchers are looking for ways to make warehouse robots smarter and more efficient by getting them to communicate and cooperate like a swarm of ants.

A swarm is just exactly what you want with warehouse robots. There are a lot of them, and they're all identical and interchangeable, cooperating to complete complex tasks by combining simple actions. The big difference between a swarm of (say) ants and a swarm of (say) robots is that the ants don't have any high-level control: each ant has its own little tiny brain, and even though ants have specific tasks that they are directed (or bred) to perform, they decide on an individual level how to go about carrying out their instructions.

What Fraunhofer is trying to do is mimic the ant swarm system with robots. For example, instead of having one central computer control the movements every robot (as with Kiva), Fraunhofer's system utilizes robots that make their own decisions with onboard computers. Each robot communicates with all the other robots in the swarm simultaneously using WLAN, and they use algorithms based on a model for how ants forage for food to cooperatively decide which of them should go where and do what. 

The robots don't need fixed localization points, but instead rely on "integrated localization and navigation technology" (including signal-based location capability, distance and acceleration sensors and laser scanners) to find the most direct routes to their destination without crashing into anything or each other. This makes them very efficient, and it also makes the system easily scalable, since you can introduce new things and the robots won't freak out.

Scalability, reliability, and flexibility are why swarm robotics has been getting so much attention lately: need a bigger system? Just toss more bots into the mix. Lose a bot to a mechanical problem? It's not a problem, since another bot just takes over. We've seen lots of swarms related to search and rescue (i.e. military) applications, but as far as a way to improve a commercial (or industrial) project, this research seems like a promising way to go.

[ Fraunhofer ] via [ Gizmag ]

TED talk: Robots that fly ... and cooperate by Vijay Kumar

TED talk: Robots that fly ... and cooperate by Vijay Kumar:

In one of the most impressive TED talks, Professor Vijay Kumar from GRASP Lab of University of Pennsylvania explains the dynamics of flying quadcopters robots. He show some of the already viral videos produced by the lab and explains some of the math that make them possible concluding with an extraordinary musical performance! - via DIYdrones.

Swarm robotics at the Science Museum

From Prof. Alan Winfield's Web Log by Alan Winfield

Swarm robotics at the Science Museum: Just spent an awesomely busy weekend at the Science Museum, demonstrating Swarm Robotics. We were here as part of the Robotville exhibition, and - on the wider stage - European Robotics Week. I say we because it was a team effort, led by my PhD student Paul O'Dowd who heroically manned the exhibit all four days, and supported also by postdoc Dr Wenguo Liu. Here is a gallery of pictures from Robotville on the science museum blog, and some more pictures here (photos by Patu Tifinger):

Although exhausting, it was at the same time uplifting. We had a crowd of very interested families and children the whole time - in fact the organisers tell me that Robotville had just short of 8000 visitors over the 4 days of the exhibition. What was really nice was that the whole exhibition was hands-on, and our sturdy e-puck robots - at pretty much eye-level for 5-year olds, attracted lots of small hands interacting with the swarm. A bit like putting your hand into an ants nest (although I doubt the kids would have been so keen on that.)

Let me explain what the robots were doing. Paul had programmed two different demonstrations, one with fixed behaviours and the other with learning.

For the fixed behaviour demo the e-puck robots were programmed with the following low-level behaviours:

1. Short-range avoidance. If a robot gets too close to another robot or an obstacle then it turns away to avoid it.
2. Longer-range attraction. If a robot can sense other robots nearby but gets too far from the flock, then it turns back toward the flock. And while in a flock, move slowly.
3. If a robot loses the flock then it speeds up and wanders at random in an effort to regain the flock (i.e. another robot).
4. While in a flock, each robot will communicate (via infra-red) its estimate of the position of an external light source to nearby robots in the flock. While communicating the robot flashes its green body LED.
5. Also while in a flock, each robot will turn toward the 'consensus' direction of the external light source.

The net effect of these low-level behaviours is that the robots will both stay together as a swarm (or flock), and over time, move as a swarm toward the external light source. Both of these swarm-level behaviours are emergent because they result from the low-level robot-robot and robot-environment interactions. While the flocking behaviour is evident in just a few minutes, the overall swarm movement toward the external light source is less obvious. In reality even the flocking behaviour appears chaotic, with robots losing each other, and leaving the flock, or several mini-flocks forming. The reason for this is that all of the low-level behaviours make use of the e-puck robots' multi-purpose Infra-red sensors, and the environment is noisy; in other words because we don't have carefully controlled lighting there is lots of ambient IR light constantly confusing the robots.

The learning demo is a little more complex and makes use of an embedded evolutionary algorithm, actually running within the e-puck robots, so that - over time - the robots learn how to flock. This demo is based on Paul's experimental work, which I described in some detail in an earlier blog post, so I won't go into detail here. It's the robots with the yellow hats in the lower picture above. What's interesting to observe is that initially, the robots are hopeless - constantly crashing into each other or the arena walls, but noticeably over 30 minutes or so we can see the robots learn to control themselves, using information from their sensors. The weird thing here is that, every minute or so, each robot's control software is replaced by a great-great-grand child of itself. The robot's body is not evolving, but invisibly it's controller is evolving, so that later generations of controller are more capable.

The magical moment of the two days was when one young lad - maybe 12 years old, who very clearly understood everything straight away and seemed to intuit things I hadn't explained - stayed nearly an hour explaining and demonstrating to other children. Priceless.

SELF-DRIVING VEHICLES SWARMING TO FUTURE ROADS

Analysis by Nic Halverson

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Schools of fish, flocks of birds -- even bicyclists in the Tour de France -- all use the principles of swarm behavior and drafting to conserve energy while moving in the same direction.

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Australian industrial designer, Charles Rattray, believes these concepts are the future of transportation. That's why he's designed Autonomo, a biomimicry inspired autonomous vehicle he hopes will revolutionize the auto industry by the year 2030.

Influenced heavily by swarm robotics and artificial intelligence, Rattray's omni-wheeled, self-driving Autonomos would travel in tight platoons while shifting their configurations to maintain an uninterrupted traffic flow. Microwave sensors would allow cars to travel a mere 7.8 inches apart, thus aerodynamically reducing vehicle drag and energy consumption, making tailgating actually a good thing.

Onboard computers would synthesize data from an array of sensors (radar, microwave, lidar, optical and infrared) and external feedback systems that would monitor the road 656 feet in front of and behind the vehicle or vehicle platoon. There's also hi-def cameras equipped with object recognition technologies that would help predict the path of other vehicles, cyclists, pedestrians and other hazardous objects.

Balancing these flocks of vehicles would be a centralized database controlled by intelligent algorithms that could adjust as new spatial information is fed to them.

Rattray's concept vehicle is a svelte 3.77 foot wide two-seater with bobsled-style seating. It's slim design would allow Autonomos to travel two abreast in a single lane so that existing road infrastructures would not need overhauling.

Vehicles would be charged wirelessly through electrodynamic induction or energy transfer lasers via charging pads embedded on the surface of the road.

BLOG: Speed Bumps You'll Be Happy To Drive Over

Obviously, this project aims to lasso the moon with an ambition of fantastical proportions. But as the great architect of Chicago, Daniel Burnham, once said, "Make no little plans. They have no magic to stir men's blood and probably themselves will not be realized."

[Via GizMag]

Credit: Charles Rattray

I, for one, welcome our new farming robots

I, for one, welcome our new farming robots:

One step closer to the robots taking over!

Wired’s Eric Smalley has an awesomely titled article about a Massachusetts based startup, Harvest Automation, is testing a small farming robot to work in nurseries in the horticulture industry.

The Harvest Automation robots are knee-high, wheeled machines. Each robot has a gripper for grasping pots, a deck for carrying pots, and an array of sensors to keep track of where it is and what’s around it. Teams of robots zip around nursery fields, single-mindedly spacing and grouping plants. Think Wall-E without the doe eyes and cuddly personality, or the little forest-tending ‘bots in the 1972 sci-fi classic Silent Running.

Thank you Wired!

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EPFL Researchers Demonstrate Flocking

EPFL Researchers Demonstrate Flocking:

The above image is taken from a video of research done by Sabine Hauert, Severin Leven, and Dario Floreano of the Laboratory of Intelligent Systems, EPFL, Lausanne, Switzerland. As part of this research, they tested the effects of turning radius and communications range on programmed flocking behavior in a group of ten aerial robots. More details are available on the Wired Science blog, and in the video.