IARPA Announces Winners
Of 3-D Mapping Challenge
The Intelligence Advanced Research Projects Activity, or
IARPA, has selected the winners of its crowdsourced MultiView Stereo 3-D Mapping Challenge—a contest to see who
could develop the best algorithms to produce accurate 3-D
maps from satellite photos.
IARPA named the challenge winners using the competitors’
handles: psyho, carlito and sdrdis. The problem solvers won
cash prizes from a total purse of $100,000.
The challenge, which drew 34 participants, was divided into
two segments. The Explorer Challenge marked the first half
of the competition, introducing contenders to the dataset and
preparing them for the follow-on Master Challenge, during
which they parlayed their Explorer Challenge experience to
design the strongest possible mapping algorithm.
The challenge goals and objectives included fostering innovation through crowdsourcing; cultivating and sustaining
a collaborative community dedicated to this research; and
stimulating communities to develop and enhance automated
methods to derive accurate 3-D point clouds from multiview
satellite imagery, including computer vision, remote sensing
U.S. Air Force Experiments
The Kill Chain Integration Branch at Hanscom Air Force
Base in Massachusetts has begun an experimentation campaign known as Data-to-Decisions to look at how to provide
warfighters data in the fastest, most efficient ways possible.
The projects under this campaign are all part of a larger
effort referred to as “combat cloud,” which uses a hybrid
cloud approach and aims to bridge the gap between different
types of data and how that data is communicated across multiple platforms.
One project the team is working on is called the Tactical
Cloud Reference Implementation, or TCRI, which puts the
architecture in place for the combat cloud. TCRI is a software
platform that will provide a common framework to manage
operational data while analyzing the data using automated
mathematical algorithms and analytics.
The Air Force, Army, Defense Threat Reduction Agency
and Navy are working on this joint program. As development
progresses, the Air Force will head the program with the Navy,
which originally led it alone.
At Forward Operating Bases
Engineers at the Massachusetts Institute of Technology
(MIT), with support from the Office of Naval Research
(ONR), have developed a portable measurement system to
precisely and inexpensively monitor the amount of electricity used by individual household appliances, lighting fixtures
Space Robotics Consortium
The Defense Advanced Research Projects Agency
(DARPA) has launched the Consortium for Execution of Rendezvous and Servicing Operations (
CONFERS) to develop technical and safety standards for
on-orbit commercial satellite servicing operations.
The standards will cover operations involving physical contact with satellites as well as robotic servicing.
DARPA aims to establish an industry and government forum made up of experts from throughout
the space community. Participants will leverage best
practices to research, develop and publish nonbinding,
The CONFERS program will be executed by an
administrative organization that will address the primary areas of consortium organization, standards
development and technical leadership and management. DARPA plans to transfer CONFERS leadership
and funding to industry before fiscal year 2021.
The International Space Station’s
Canadarm2 robotic arm is a bigger,
better, smarter version of the robotic
arm that was on the space shuttles.
and electronic devices. The system could be a valuable tool
for the military, the researchers say, noting that it could
uncover ways to save energy in heating or cooling forward
Researchers placed five postage stamp-size, self-calibrat-ing sensors above or near power lines coming into a house,
enabling them to automatically pinpoint the strongest electrical signals.
The system can distinguish between each type of light,
appliance and device based on unique signatures and show
which ones turn on and off, how often and at what times.
Users can then view the real-time data on an app and focus on
specific time segments—revealing when, for example, a refrigerator goes into its defrost cycle.