Knightscope recently announced it is developing technology to predict and prevent crime utilizing autonomous robots and predictive analytics. Crime has a $1 trillion negative economic impact on the US each year, and it is Knightscope’s mission to cut that in half with its new K5 Autonomous Data Machine.
Knightscope’s K5 is built on the Segway RMP220, a powerful and highly maneuverable two-wheeled dynamically stable platform, which allows for obstacle avoidance, path planning and human-robot interaction. The RMP220 can travel up to 10 mph, is industrial grade, has a zero turning radius and offers a human-height point of view to provide a commanding physical presence and to fully leverage the K5’s extensive sensor payload.
Each K5 features an integrated operating system that guides the unit autonomously through defined boundaries enabling it to collect real-time data from the unit’s immediate surroundings.
The K5 accommodates a wide range of sensor options including nighttime and daytime omnidirectional cameras, ambient noise microphones, optical character recognition, thermal imaging, air quality, ultrasonic, lasers and more. Data collected through these sensors is processed through Knightscope’s predictive analytics engine, combined with existing business, government and social data sets, and subsequently assigned a threat level that determines when an alert should be pushed.
“Knightscope chose Segway’s RMP220 as the base for its crime fighting robots to enable easy scaling of our K5 Autonomous Data Machines as well as to support our fast go-to-market strategy,” said Arne Stoschek, Vice President of Engineering, Knightscope. “Additional factors in our decision to implement the RMP220 included its outstanding maneuverability, extended battery life and long-term durability.”
Knightscope will revolutionize safety by crowd sourcing security. By making data streams public upon any alert and allowing the community to engage and contribute in the process, Knightscope maintains transparency and strengthens the ability to reduce crime.
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Segway Inc. recently brought on Manu Systems AG, located in Regensburg Germany, as a European reseller of its Robotics Mobility Platforms (RMPs). Manu Systems AG is well known as one the region’s leading value-added resellers of robotic hand systems, humanoid robots and other robotics mobility systems.
“We are pleased to be working with Segway. Our mission is to provide a one-stop shopping experience for service robotics researchers,” said Marco Reichel, Chairman of the Management Board, Manu Systems. “Our offering of Segway’s RMPs has been very well received by the European research market.”
Manu Systems AG currently offers Segway’s RMP 50 Omni and 50 XL, RMP 200 and 200 ATV, RMP 400, 400 Omni and RMP 440. For more information on these platforms, please visit Manu Systems AG’s website or contact the company by phone: +49 941 9459 280 or e-mail.
Marathon Targets (http://www.marathon-targets.com/) successfully demonstrated their smart target system during a live fire demonstration at Quantico Marine Base. Marathon’s systems are developed on both the Segway RMP200 and RMP400. To view a short video of the demonstration, click here.
For more information on the full line of Segway’s robotic platforms, please visit http://rmp.segway.com/.
The Segway RMP 400 is our most powerful mobile robot platform. Powered by four lithium-ion battery packs and rolling on four ATV tires, the Segway RMP 400 is a mobile workhorse capable of carrying up to 400 lbs for long distances, over challenging terrain.
All Segway unmanned ground vehicles are designed for easy integration by scientists and engineers and are the ideal starting point for applications including research and development, industrial automation, security, and defense.
For more information or to request a quote, click here.
These images were taken during the 2010 Robotics Rodeo at Ft. Benning.
HERB is a mobile manipulation platform built on a Segway RMP by Intel Research Pittsburgh, in collaboration with the Robotics Institute at Carnegie Mellon University. HERB can perform real-world tasks, such as opening refrigerator and cabinet doors, finding and collecting coffee mugs, and throwing away trash. HERB is powered by ROS and a variety of open-source libraries, including several developed by CMU researchers, like OpenRAVE and GATMO
For more info on HERB, read this article at eweek.com
Segway Inc. will supply its RMP mobile robot platforms to Marathon Robotics as part of a $50 Million contract with the U.S. Marine Corps (USMC).
Marathon Robotics has spent the last 8 year perfecting an integrated system of target practice mobile robots that will revolutionize the quality and effectiveness of live-fire training. The Segway RMP continues to be their preferred mobile robot platform due to its speed, agility, and robustness.
For more information, please see the Marathon Robotics press release
The Australian Research Council (ARC) Centre for Autonomous Systems (CAS) entered the RoboCup@Home competition this year with a new personal assistance robot built on a Segway RMP 100 mobile robot platform. The CAS is the second largest robotics research group in the world with representation from the University of Sydney, the University of New South Wales and the University of Technology Sydney
The RoboCup@Home competition judges navigation, mapping, object recognition, and human-robot interaction in realistic, home-like environments. RoboCup@Home is the largest international annual competition for autonomous service robots.
The GPS and Vehicle Dynamics Laboratory at Auburn University (GAVLAB) and the Army Corp of Engineers Huntsville Center developed an RMP 400 based mobile robot system capable of autonomously mapping a given field for the purpose of finding unexploded ordnance (UXO). A combination of GPS and INS are used for navigation, while the trailer carries two Geonics EM61-Mk2 metal detectors. The video below shows the robot in action at a range in the Great Salt Plains area of Oklahoma.
Using an RMP 400 as a test bed, Idaho National Lab (INL) and the Robotics Research Group at the University of Texas at Austin (RRG) integrated INL’s modular control software, RIK (Robot Intelligence Kernel) with RRG’s manipulation control software framework, OSCAR (Operational Software Components for Advanced Robotics) to develop an improved interface for robotic operation and control of mobile manipulation. The resulting system improves operator effectiveness by supplementing teleoperated control with optional automation of tasks such as navigation and target acquisition.