Invention: UAV swarms

* 13:12 28 August 2007
* NewScientist.com news service
* Justin Mullins

The skies above future battlefields are likely to be filled with unmanned aerial vehicles (UAVs) monitoring the action and homing in on enemy targets. But how do you control a sky full of UAVs, particularly when communications links with the ground are patchy?

Perhaps you don't have to. Yossi Ben-Asher and colleagues at the Technion-Israel Institute of Technology in Haifa, Israel, say UAVs can control themselves instead.

Their idea is for a swarm of UAVs to create its own communications network and swap the information needed to calculate flight paths and avoid collisions. This not only eliminates the need for constant communication with the ground, it can also be used to make the aircraft swarm together, like a flock of birds.

This swarming behaviour can then be used to mount more effective attacks, the team says. The UAVs could monitor a target and decide for themselves how best to attack it, based on the position of each aircraft and the weapons it is carrying.

The patent application stops short of explaining how the final decision to engage is taken. Presumably somebody on the ground has to give the go-ahead. But how long before technology like this makes the military think it can dispense with even this step?

Read the full swarming UAVs software patent application.

News: Autonomous vehicle finds way without GPS

In the European Land Robot Trial, a vehicle of the university of the German armed forces (Universitaet der Bundeswehr) is the winner in the speed discipline. In comparison the Darpa Grand Challenge, the European contest demands more autonomy, participants say.

The vehicle used by the university's team was a Volkswagen Tuareg, the same type that already has won last year's Grand Challenge. Basically, the vehicle even was equipped very similarly, but in contrast to the Darpa Grand Challenge where the vehicles drive along a track that connects waypoints, defined by GPS navigation, the European Land Robot Trial does not allow the intensive use of satellite navigation.


EE Times Europe: Autonomous vehicle finds way without GPS - Link
European Land-Robot Trial (ELROB) Website - Link
Wikipedia: ELROB - Link

New devices promise touchy-feely computing

Full content

Is it possible to "feel" an object while being in another location? This is a question addressed by several technologies on show at the SIGGRAPH 2007 computer conference in San Diego, California, US, earlier this month.

Box of balls
Gravity Grabber, this prototype device consists of two tube-shaped attachments that fit over a person's thumb and forefinger. Each tube has a pair of motors that sit on top and connect to a belt that wraps around the tip of the finger. The motors can pull on the belt to produce the feeling of touching an object, and can produce the feeling of holding something heavy by pulling more tightly.

Gravity Grabber in action

ICAR2007 : Robot positioning using structured light patterns suitable for self calibration and 3D tracking

Title : Robot positioning using structured light patterns suitable for self calibration and 3D tracking

Author : Kasper Claes, Herman Bruyninckx

Abstract : We study the control of a robot arm with an eye-in-hand camera, using structured light with a projector in a fixed but unknown position. Based on the theory of perfect maps, we propose a deterministic method to generate patterns independent of the relative 6D orientation between the camera and the projector, with any alphabet size and minimal Hamming distance between the codes. This independence makes self calibration using a known robot motion possible, and removes the need for less robust calibration grids. Patterns that are large enough for controlling a robotic arm are generated with error correcting capabilities. The experiments show the controlled motion of an industrial robot to a chosen position near a non-planar object, using a projector-camera calibration. This provides a wider baseline and hence more robustness than structure from motion.

Lab Meeting 27 August (Chihao): Demonstration of Acoustic Localization in PAL2

I will show the acoustic localization system in PAL2.
This system could find the direction of sound audio source even if the source is moving.

Lab Meeting 27 August (Atwood): Recognition by Local Feature

I will talk about two works on recognition by local features and my recent experiments

Jerry Jun Yokono, Tomaso Poggio. A Multiview Face Identification Model With No Geometric Constraints. In Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition (FGR06)

Ariadna Quattoni, Michael Collins and Trevor Darrel. Conditional Random Fields for Object Recognition. In Advances in Neural Information Processing Systems 17 (NIPS 2004), 2005.

Lab Meeting 27 August (fish60): Speeding up Moving-Target Search

Abstract:

In this paper, we study moving-target search, where an agent has to catch a moving target . The agent does not necessarily know the terrain initially but can observe it within a certain sensor range around itself.
It uses the strategy to always move on a shortest presumed unblocked path toward the target. We study how the agent can find such paths faster by exploiting the fact that it performs A* searches repeatedly.
To this end, we extend Adaptive A* to moving-target search and demonstrate experimentally that the resulting MT-Adaptive A* is faster than isolated A* searches.

Link

News: LucidTouch - A See-Through Mobile Device

Softpedia - Windows Aero Is Old News - Link
Engadget - Microsoft R&D strikes again: the LucidTouch - Link

News: iRobot's new Roomba 560, 530: totally redesigned vacuumbots

iRobot hasn't released a new, proper Roomba servantbot since late 2004's Discovery (Scooba, of course, excepted). Today that changes, with the 560 and 530 we caught wind of back in May. There's a lot going on here, so we'll start at the top:

• iRobot is touting these new Roombas as being "totally redesigned" from the ground up.
• The new vacuum system is supposedly 100% more effective at picking up the grime in your floors. Really makes the old model suck. Thanks, we'll be here all week.
• The 560 features 2.4GHz RF that activates its new Virtual Wall Lighthouse system (we'll get to that in a sec. The 530 doesn't have RF.
• Scheduling is now built into the robot. Friggin FINALLY!
• The new Roombas have IR sensors built into the bumper, and have a second, slower running speed. When Roomba is approaching an object, it slows down so as not to bump it so hard.
• Lighthouses are Roomba's new RF-based progress tracking system. Place one in each doorway, and they switch on via RF when your Roomba does. When Roomba's done with a room, it won't re-enter until the next time it runs.
• The battery is still removable, but you have to unscrew the bottom plate to get it out. Oh, and now you can add faceplates.
• The system is far better sealed off, so most of the crap you're vacuuming up supposedly won't actually get inside the robot anymore. Extra bonus: that black arc between the bumper and buttons is a handle that lies flush.
• The 560 goes for $350, the 530 goes for $300 -- snag 'em both starting now.

engadget: iRobot's new Roomba 560, 530 - Link
iRobot Corporation - Link

News: The DIY Segway

A tenacious combination of high school and MIT students have put together their very own DIY Segway, which would likely have Dean Kamen rolling in his grave... if he were actually dead. The team of ingenious do-it-yourself'ers put together a fairly workable Segway knock-off for less than a thousand dollars that can keep pace with the actual model (11 MPH versus the real-deal's 12.5). By using off-the-shelf supplies, like a Machine Science XBoard microcontroller, pieces of Lexan for the steering mechanism, and light, cheap aluminum for the frame, the gang was able to assemble a fairly stripped down version of the scooter. Apparently, the kids are still working out the kinks, but if this keeps up, Kamen and crew might have to start watching their backs. Check the video after the break to see the still-shaky personal transporter in action. - [via] Link

News: Nao bot chosen as AIBO RoboCup replacement

In a rather strange move, French start-up Aldebaran, and their Nao humanoid robot, has been chosen as the replacement competitor for the discontinued Sony AIBO. The two-legged Nao will replace the four-legged AIBO in the Standard Platform League (formerly the Four-Legged League) of RoboCup, the popular robotic soccer competition. It seems something of a curious choice, given the fact that Aldebaran hasn't even shipped a product yet. - [via] Link

Aldebaran Robotics - Link

Weight Loss Robot Will Shame You Into Eating Less

Hey, chubster. Do you have trouble keeping a healthy diet? Would having a friendly, diet-focused robot in your kitchen help? No? Well, don't tell the guys at the MIT Media Lab that, because that's exactly what they've been cooking up. It's an in-home robot that'll make eye contact with you while it tracks your eating habits and shuns you for constantly nibbling on Doritos rather than carrot sticks. It's like a nagging spouse, but it doesn't have the personal investment of having to see you naked. I'm not sure if that's a plus or a minus in its favor.

link

[VASC Seminar Series ]Video Summarization for PVRs

Speaker: Ajay Divakaran, MERL

Time: Wednesday August 15, 12-1pm

Abstract:

We present the world's first highlights-playback-capable Hard Disk Drive
(HDD)-enhanced DVD recorder. It automatically detects highlights in sports
video by detecting portions with a mixture of the commentator's excited
speech and cheering, using Gaussian Mixture Models (GMM's) trained using
the MDL criterion. Our computation is carried out directly on the MDCT
coefficients from the AC-3 coefficients thus giving us a tremendous speed
advantage. Our accuracy of detection of sports highlights is high across a
variety of sports. Our user-study shows that viewers like the new
functionality even if it makes mistakes. Finally, we propose
genre-independent temporal segmentation of non-sports content using
computationally inexpensive audio-visual features. Such segmentation
enables "smart skipping," from one semantic unit to another.

project link

[Book] Face Recognition

Title: Face Recognition

About the Book:

… this book will serve as a handbook for students, researchers and practitioners in the area of automatic (computer) face recognition and inspire some future research ideas by identifying potential research directions. The book consists of 28 chapters, each focusing on a certain aspect of the problem. Within every chapter the reader will be given an overview of background information on the subject at hand and in many cases a description of the authors' original proposed solution. The chapters in this book are sorted alphabetically, according to the first author's surname. They should give the reader a general idea where the current research efforts are heading, both within the face recognition area itself and in interdisciplinary approaches.

the full text of this book

Lab Meeting 13 August (Yu-Chun): Emotional Architecture for the Humanoid Robot Head ROMAN

2007 IEEE International Conference on Robotics and Automation

Author: Jochen Hirth, Norbert Schmitz and Karsten Berns

Abstract:
Humanoid robots as assistance or educational robots is an important research topic in the field of robotics. Especially the communication of those robots with a human operator is a complex task since more than 60% of human communication is conducted non-verbally by using facial expressions and gestures. Although several humanoid robots have been designed it is unclear how a control architecture can be developed to realize a robot with the ability to interact with humans in a natural way. This paper therefore presents a behavior-based emotional control architecture for the humanoid robot head ROMAN. The architecture is based on 3 main parts: emotions, drives and actions which interact with each other to realize the human-like behavior of the robot. The communication with the environment is realized with the help of different sensors and actuators which will also be introduced in this paper.

Link

Lab Meeting 6 August (Jim): Fast Replanning for Moving-Target Search

Talk by Sven Koenig

I will try to talk about this part: Fast Replanning for Moving-Target Search

MT-Adaptive A*, an incremental variant of A* that updates the heuristics between searches. MT-Adaptive A* is faster than isolated A* searches and, in many situations, also D* Lite, a state-of-the-art incremental variant of A*.

See here for more information http://idm-lab.org/project-a.html
(Speeding up Moving-Target Search)

Talk by Sven Koenig; Tuesday August 7

SPEAKER: SVEN KOENIG (http://idm-lab.org/)
Computer Science Department, University of Southern CaliforniaPICTURE: See http://idm-lab.org
TITLE: ADVANCES IN PATH PLANNING
DATE: August 7, TuesdayTIME: 10:30am-11:30am
LOCATION: Newell Simon 1305
FACULTY HOST / APPOINTMENTS: Eugene Fink (e.fink@cs.cmu.edu )


ABSTRACT:
An Overview of two of currentresearch projects on path planning for video games, namely, any-anglepath planning and fast replanning for moving-target search.


Any-Angle Path Planning:
Theta*, a variant of A* that propagates information along grid edges without constraining the paths to grid edges. Theta* is simple, fast and finds short and realistic looking paths.


Fast Replanning for Moving-Target Search:
MT-Adaptive A*, anincremental variant of A* that updates the heuristics between searches. MT-Adaptive A* is faster than isolated A* searches and, in many situations, also D* Lite, astate-of-the-art incremental variant of A*.



Additional information about Sven can be found on his web pages: idm-lab.org.

[Master Thesis] Incremental learning for Adaptive Visual Place Recognition in Dynamic Indoor Environments

Author:
Jie Luo,
Department of Computer and Systems Sciences,
Stockholm University / Royal Institute of Technology

Summary:
Vision-based place recognition is a desirable feature for an autonomous mobile system. In order to work in realistic scenarios, a visual recognition algorithm should have two key properties: robustness and adaptability. This thesis focuses on the latter, and presents a discriminative incremental learning approach to place recognition. We propose a solution based on incremental extensions of support vector machine classifier. Since computational and memory efficiency are crucial for mobile robot platforms aim to continoulsy work in real-world settings, we put emphasis on these properties. We use a recently introduced memory-controlled incremental technqiue, which allows to control the memory requirements as the system updates its internal representation. At the same time, it preserves the recognition performance of the batch algorithm and runs online. In order to assess the method, we acquired a database capturing the intrinsic variability of places over time. Extensive experiments show the power and the potential of the approach.

Moreover, the feature space of SVM consists of both global feature - Composed Receptive Field Histograms, and local features - Harris-Laplace Detector and SIFT Descriptor.

fulltext

CVPR 07 Awards

Longuet-Higgins Prize

* J. Shi and J. Malik, Normalized Cuts and Image Segmentation
* E. Osuna, R. Freund, and F. Girosi, Training Support Vector Machines: An Application to Face Detection

Best Paper Prize

* B. Leibe, N. Cornelis, K. Cornelis, and L. van Gool, Dynamic 3D Scene Analysis from a Moving Vehicle

Best Paper Prize Runner Ups

* A. Levin, A. Rav Acha, and D. Lischinski, Spectral Matting
* O. Tuzel, F. Porikli, and P. Meer, Human Detection via Classification on Riemannian Manifolds

Best Student Paper Prize

* Y. Li, H. Ai, T. Yamashita, S. Lao, and M. Kawade, Tracking in Low Frame Rate Video: A Cascade Particle Filter with Discriminative Observers of Different Lifespans

CNN news: Concept car gets testy with drunk drivers

A new concept car with breathalyser-like detection systems may provide even greater traction for Japanese efforts to keep impaired drivers off the road.

Nissan's alcohol-detection sensors check odor, sweat and driver awareness, issuing a voice alert from the navigation system and locking up the ignition if necessary.

Odor sensors on the driver and passenger seats read alcohol levels, while a detector in the gear-shift knob measures the perspiration of the driver's palm when starting the car.
...
But Nissan's car includes a mounted camera that monitors alertness by eye scan, ringing bells and issuing a voice message in Japanese or English if a driver should pull over and rest.

See the full article.