Robot Technology News  
ROBO SPACE
New standard helps optical trackers follow moving objects precisely
by Staff Writers
Washington DC (SPX) Nov 25, 2016


In this segment of the "NIST in 90" series, host Chad Boutin and NIST engineer Roger Bostelman demonstrate why it's important to evaluate how well optical tracking systems can place an object, such as a mobile robot in a factory, in 3-D space. Image courtesy NIST. Watch a video on the research here.

Throwing a perfect strike in virtual bowling doesn't require your gaming system to precisely track the position and orientation of your swinging arm. But if you're operating a robotic forklift around a factory, manipulating a mechanical arm on an assembly line or guiding a remote-controlled laser scalpel inside a patient, the ability to pinpoint exactly where it is in three-dimensional (3-D) space is critical.

To make that measurement more reliable, a public-private team led by the National Institute of Standards and Technology (NIST) has created a new standard test method to evaluate how well an optical tracking system can define an object's position and orientation - known as its "pose" - with six degrees of freedom: up/down, right/left, forward/backward, pitch, yaw and roll.

Optical tracking systems work on a principle similar to the stereoscopic vision of a human. A person's two eyes work together to simultaneously take in their surroundings and tell the brain exactly where all of the people and objects within that space are located. In an optical tracking system, the "eyes" consist of two or more cameras that record the room and are partnered with beam emitters that bounce a signal - infrared, laser or LIDAR (Light Detection and Ranging) - off objects in the area. With both data sources feeding into a computer, the room and its contents can be virtually recreated.

Determining the pose of an object is relatively easy if it doesn't move, and previous performance tests for optical tracking systems relied solely on static measurements. However, for systems such as those used to pilot automated guided vehicle (AGV) forklifts - the robotic beasts of burden found in many factories and warehouses - that isn't good enough. Their "vision" must be 20/20 for both stationary and moving objects to ensure they work efficiently and safely.

To address this need, a recently approved ASTM International standard (ASTM E3064-16) now provides a standard test method for evaluating the performance of optical tracking systems that measure pose in six degrees of freedom for static - and for the first time, dynamic - objects.

NIST engineers helped develop both the tools and procedure used in the new standard. "The tools are two barbell-like artifacts for the optical tracking systems to locate during the test," said NIST electronics engineer Roger Bostelman. "Both artifacts have a 300-millimeter bar at the center, but one has six reflective markers attached to each end while the other has two 3-D shapes called cuboctahedrons [a solid with 8 triangular faces and 6 square faces]." Optical tracking systems can measure the full poses of both targets.

According to Bostelman's colleague, NIST computer scientist Tsai Hong, the test is conducted by having the evaluator walk two defined paths - one up and down the test area and the other from left and right - with each artifact. Moving an artifact along the course orients it for the X-, Y- and Z-axis measurements, while turning it three ways relative to the path provides the pitch, yaw and roll aspects.

"Our test bed at NIST's Gaithersburg, Maryland, headquarters has 12 cameras with infrared emitters stationed around the room, so we can track the artifact throughout the run and determine its pose at multiple points," Hong said. "And since we know that the reflective markers or the irregular shapes on the artifacts are fixed at 300 millimeters apart, we can calculate and compare with extreme precision the measured distance between those poses."

Bostelman said that the new standard can evaluate the ability of an optical tracking system to locate things in 3-D space with unprecedented accuracy. "We found that the margin of error is 0.02 millimeters for assessing static performance and 0.2 millimeters for dynamic performance," he said.

Along with robotics, optical tracking systems are at the heart of a variety of applications including virtual reality in flight/medical/industrial training, the motion capture process in film production and image-guided surgical tools.

"The new standard provides a common set of metrics and a reliable, easily implemented procedure that assesses how well optical trackers work in any situation," Hong said.

The E3064-16 standard test method was developed by the ASTM Subcommittee E57.02 on Test Methods, a group with representatives from various stakeholders, including manufacturers of optical tracking systems, research laboratories and industrial companies.


Comment on this article using your Disqus, Facebook, Google or Twitter login.


Thanks for being here;
We need your help. The SpaceDaily news network continues to grow but revenues have never been harder to maintain.

With the rise of Ad Blockers, and Facebook - our traditional revenue sources via quality network advertising continues to decline. And unlike so many other news sites, we don't have a paywall - with those annoying usernames and passwords.

Our news coverage takes time and effort to publish 365 days a year.

If you find our news sites informative and useful then please consider becoming a regular supporter or for now make a one off contribution.
SpaceDaily Contributor
$5 Billed Once


credit card or paypal
SpaceDaily Monthly Supporter
$5 Billed Monthly


paypal only


.


Related Links
National Institute of Standards and Technology
All about the robots on Earth and beyond!






Share this article via these popular social media networks
del.icio.usdel.icio.us DiggDigg RedditReddit GoogleGoogle

Previous Report
ROBO SPACE
New AI algorithm taught by humans learns beyond its training
Toronto, Canada (SPX) Nov 18, 2016
"Hey Siri, how's my hair?" Your smartphone may soon be able to give you an honest answer, thanks to a new machine learning algorithm designed by U of T Engineering researchers Parham Aarabi and Wenzhi Guo. The team designed an algorithm that learns directly from human instructions, rather than an existing set of examples, and outperformed conventional methods of training neural networks by ... read more


ROBO SPACE
DARPA doubles down on Tern by funding 2nd test vehicle

State Dept. approves sale of 26 Predator B drones to U.K.

India's Rustom-II combat UAV completes first flight test

A tethered drone-based asset management solution

ROBO SPACE
NASA microthrusters achieve success on ESA's LISA Pathfinder

Sweden orders new laser simulators from Saab

Calculations predict unexpected disorder in the surface of polar materials

New clues emerge in 30-year-old superconductor mystery

ROBO SPACE
Making spintronic neurons sing in unison

World's fastest quantum simulator operating at the atomic level

Tracking the flow of quantum information

Breakthrough in the quantum transfer of information between matter and light

ROBO SPACE
Vietnam scraps huge nuclear power plant projects

French power company EDF underestimating costs: study

Finnish client 'alarmed' by French nuclear industry overhaul

Time to tackle the UK's plutonium mountain

ROBO SPACE
ICC eyeing foreign fighters in Syria, Iraq

French priest reveals IS child jihadist training

Balkan weapon trafficking still a major problem; 2015 terror deaths fall

European 'concern' over returning jihadist fighters: Belgium

ROBO SPACE
China power plant collapse kills at least 22: Xinhua

Climate: Four nations map course to carbon-free economies

Study: LED lights draw fewer insects

Shifting focus leaves mixed bag for German utility RWE

ROBO SPACE
Glow-in-the-dark dye could fuel liquid-based batteries

Researchers report new thermoelectric material with high power factors

EAST achieves longest steady-state H-mode pperations

First observations of tongue deformation of plasma

ROBO SPACE
Material and plant samples retrieved from space experiments

Chinese astronauts return to earth after longest mission

China completes longest manned space mission yet

Chinese astronauts accept 1st earth-space interview









The content herein, unless otherwise known to be public domain, are Copyright 1995-2024 - Space Media Network. All websites are published in Australia and are solely subject to Australian law and governed by Fair Use principals for news reporting and research purposes. AFP, UPI and IANS news wire stories are copyright Agence France-Presse, United Press International and Indo-Asia News Service. ESA news reports are copyright European Space Agency. All NASA sourced material is public domain. Additional copyrights may apply in whole or part to other bona fide parties. All articles labeled "by Staff Writers" include reports supplied to Space Media Network by industry news wires, PR agencies, corporate press officers and the like. Such articles are individually curated and edited by Space Media Network staff on the basis of the report's information value to our industry and professional readership. Advertising does not imply endorsement, agreement or approval of any opinions, statements or information provided by Space Media Network on any Web page published or hosted by Space Media Network. General Data Protection Regulation (GDPR) Statement Our advertisers use various cookies and the like to deliver the best ad banner available at one time. All network advertising suppliers have GDPR policies (Legitimate Interest) that conform with EU regulations for data collection. By using our websites you consent to cookie based advertising. If you do not agree with this then you must stop using the websites from May 25, 2018. Privacy Statement. Additional information can be found here at About Us.