Technology adapting robots to ever more interesting applications advances almost daily. I’m not concerned with the dystopian robots taking over for humans meme, but we are definitely in the age of robots and humans working closely together to accomplish more and better tasks.
This advancement in sensing technology comes from BeBop Sensors—smart fabric sensor technologies.
A NERVOUS SYSTEM FOR ROBOTS
Less than 1mm Thick Advanced Fabric-Based Sensor Skin
Exceeds Human Abilities for Spatial Resolution & Sensitivity
Fits Any Body Part of Humanoid Robot or Prosthetic
BeBop Sensors, www.bebopsensors.com the world leader in smart fabric sensor technologies, announced RoboSkin line of skin-like coverings for tactile awareness for humanoid robots and prosthetics. A true nervous system for robots at less than 1mm thick, RoboSkin is the only technology that fits all robotic body parts: limbs, fingers, feet, head, and torso, to make robots “feel” better. RoboSkin’s advanced fabric-based sensor skin can be shaped to any surface allowing quick tailoring to fit any robot, with spatial resolution and sensitivity that exceeds human abilities for a true partnership between humans and their robot helpers.
Why we need not fear robots replacing humans—we’ll need them.
The Census Bureau predicts that for the first time ever, there will be more Americans over the age of 65 than under 18, with Japan having the oldest population with 30% over 65. In addition, “The Great Resignation” shows no sign of slowing down, with record numbers of people leaving the work force. Human-like robots are stepping up to this urgent need, augmenting humans in the workplace, hospitals, and homes; with roles in healthcare, as domestic help, in manufacturing, distribution, biohazards, and even in entertainment and companionship roles. A human shape ensures a robot should be able to perform any human task; to fit through any door and use every human tool. Robots do not need to have the environment made around their needs — robots can do jobs humans want to avoid.
Founder Keith McMillen said, “I have been working with roboticists refining our RoboSkin for 10 years. We are pleased we can make this important contribution to the worldwide effort to bring humanoid robots into our lives to help people live longer, healthier, and more enjoyable lives.”
RoboSkin is available immediately for a variety of applications in robotics and prosthetics, including biohazard, digital health, IoT, VR/AR, automotive, law enforcement, testing, and more. For more information, see the video.
BeBop Sensors’ Founder & CTO, Keith McMillen started and sold two companies in his 40+ years innovating in the sensor and audio market. Zeta Music revolutionized stringed instruments and was sold to Gibson Guitars in 1992. Octiv, started in 2000, received funding from 3i and Intel Capital and was sold to Plantronics (NYSE:PLT) in 2005. McMillen is the inventor on numerous patents, has released hundreds of profitable products and published dozens of scholarly papers; as well as winning a Guthman Award in 2010. He received a BS in Acoustics from University of Illinois at Urbana.
I’ve felt DataOps was destined to be an important data management tool since I was introduced to it a few years back. Hitachi Vantara is one of two companies I follow specifically bringing this technology to industrial applications. Here it introduces a new portfolio bringing IIoT specifically into the core working with digital twins, machine learning (ML), and user interface.
Background. Ultimately, most industrial IoT difficulties are rooted in data management shortcomings. However, these challenges are not the same as those faced in a purely IT setting. For example, operational technology (OT) data is high-velocity time series and event information that many times lacks the detailed metadata descriptors and features needed to leverage it outside of the operations organization. In comparison, business IT data comes across in batches or transaction records with different metadata descriptors where time-stamp references are not always correlated. Merging these datasets, in context, is not trivial work, but, if done right, yields new operational insights that can provide a competitive advantage.
Lumada Industrial DataOps automates the process of abstracting, tagging, and rationalizing IT and OT data and organizes it in the data lake or data warehouse so it is usable for analysis and building AI and ML solutions. Data pipelines are established, and multiple transformations and inferences can be calculated and orchestrated as part of the workflow. Industrial process engineers can work with data scientists, analysts, and applications consultants to unlock the combined value and make major operations improvements.
But reality hasn’t lived up to the promise, and industrial operations have had a mixed relationship with IoT technologies. While there has been considerable success at the project level, broad IIoT deployments and the resulting analytics capabilities have progressed in fits and starts. Enterprises will need to leverage IIoT as well as AI and ML technology across far more use cases to better support their existing workforce and overcome supply chain issues. It turns out that it is more complicated than developers anticipated to scale their IIoT proofs of concept to stretch across a company.
The Lumada Industrial DataOps portfolio adds IIoT Core software with IIoT platform framework capabilities. The new toolkit is delivered as IIoT Analytics to accelerate the convergence of traditional IT with expanding IIoT data sources and bring powerful new software-based capabilities to life. IIoT Analytics offers prepackaged modules that provide data integration and preconfigured functions that give you a faster start on your application so you can focus on fine-tuning it for your specific requirements. A typical IIoT Analytics toolkit includes:
Digital twins for data and asset organization
ML models for faster assembly
Simulation software interfaces for greater accuracy
ML services framework for deploying AI/ML applications
Lumada Industrial DataOps directly addresses the four key challenges that hinder the enterprise-wide expansion of IIoT applications.
Challenge 1: The Need for High-Level Data Management Organizations need solutions that make it possible to access data in motion and at rest from the widest array of sources, integrate all that data, transform the data, and perform analysis. While all that happens, data security must be maintained and policies enforced to adhere to compliance and governance requirements.
Challenge 2: Automating Data Organization To create an efficient production pipeline for AI models, data scientists and analysts need an environment within which they can organize data and build models to detect events. This requires a system that automates the data analysis function, rejecting noise and providing people with a rich data signal that can be predictive or prescriptive in context.
Challenge 3: Accelerate the Training of AI Models Starting every model from scratch is not practical, as this approach may introduce delays and costs that get in the way of meeting business objectives. Data science personnel instead need templates that provide a proven foundation that they can then refine and adapt to meet specific requirements in a timely manner.
Challenge 4: Shorten Application Delivery Time Engineers and developers also need ready-made application components that provide a starting point.
Using Lumada Industrial DataOps, organizations can accelerate their development of digital twins, which can be further combined with new AI and ML analytic templates that address a variety of critical industrial activities. These analytics include anomaly detection and prediction capabilities for maintenance and operations effectiveness. These data management and application building blocks support the many industry-specific solutions offered by Hitachi to speed cooperative deployment efforts for Hitachi clients and partner organizations.
Lumada Industrial DataOps embraces the synergistic srelationships between data management, AI applications, and the next-level decision-making required in modern industrial environments. With Lumada Industrial DataOps, Hitachi empowers industrial enterprises to move their IIoT-driven AI applications out of the endless pilot phase and more quickly develop and scale for enterprise-wide deployment.
Emerson’s acquisitions have moved it more firmly into discrete manufacturing operations. This news of a new programmable automation controller family of products manages to combine benefits of control, automation, industrial Internet of Things (IIoT), analytics while “minimizing the need for specialized software engineering talent.” Automation suppliers have been on a fervent journey toward providing products that are easier to use for talent-strapped customers. It also brings in current requirements for security and open protocols.
Emerson, a global software, technology and engineering leader, announced the release of its PACSystems RSTi-EP CPE 200 programmable automation controllers (PAC). CPE 200 controllers will deliver large programmable logic controller (PLC) capability in a small, cost-effective, IIoT-ready form factor so machine manufacturers do not need to sacrifice performance for price.
Providing features that help speed time to use, the CPE 200 series offers security-by-design, open programming, and open communications built in to simplify connectivity to external analytics software platforms while reducing cost and complexity for OEMs and end users.
“Gaining competitive edge in today’s marketplace means having the flexibility to connect to the wide array of equipment end users employ as part of their proprietary processes, and supporting secure, open connectivity to allow easy access to on-premises and cloud-hosted analytics platforms,” said Jeff Householder, president of Emerson’s machine automation solutions business. “The CPE 200 series controllers take advantage of Emerson’s cybersecure-by-design architecture, common programming capabilities, and IIoT readiness to provide options currently missing in legacy compact PLCs.”
The controllers offer open communications through native, pre-licensed support for OPC UA Secure and other common industrial protocols for flexible connectivity over high-speed Gigabit Ethernet. IEC 61131 programming languages and C, the world’s most popular and easiest-to-use programming language, help engineers write and run the high-performance algorithms that enable proprietary production strategies and advanced automation technologies.
We in the US celebrate Independence Day today in commemoration of the adopting and signing the Declaration of Independence of the British colonies in part of North America from British rule.
This advice fits as well for all the international readers of this blog as for citizens and sojourners here: take some time to slowly and carefully read the actual Declaration of Independence, the Constitution of the US, and the Federalist Papers.
Digest these words from the Declaration–We hold these truths to be self-evident, that all men are created equal, that they are endowed by their Creator with certain unalienable rights, that among these are Life, Liberty and the Pursuit of Happiness.
For me “all men” means, well, all men. Also for me (as endowed later in the Constitution), all men means all humans. Yes, even women. And I am shocked and dismayed that after all these years of the movements of the mid-60s for civil rights and rights for women we still have not reached the goal. Actually, not even for all white men, either.
It seems to be a birthright of Americans to talk loudly about freedoms. It has always been my role to point out (not original with me, just read what the founders had to say!) the importance responsibility plays as the companion of freedom bringing it to its full flourishing. Seth Godin wrote today on responsibility–Demand responsibility.
I’d like to add one other idea I picked up from Andy Stanley this morning during my brisk walks around our ponds. Integrity. We have so many leaders at all levels of society lacking integrity. And that includes only the ones we hear about. Integrity belongs alongside responsibility as requirements for true freedom.
Which begs the question–where am I on the scale of responsibility and integrity? And you?
What good is an open business digital platform like Siemens’ new Xcelerator without visualization. An interface from digital to machine to human must be part of the package. While Siemens CEO Roland Busch introduced and extolled the Xcelerator platform, he brought to the set Jensen Huang, founder and CEO of Nvidia. They announced a partnership to bring the metaverse to industrial applications. The companies will connect NVIDIA Omnivores with Siemens Xcelerator “to enable full-fidelity digital twins and connect software-defined AI systems from edge to cloud.”
Why?
The addition of Omniverse to the open Siemens Xcelerator partner ecosystem will accelerate the use of digital twins that can deliver productivity and process improvements across the production and product lifecycles. Companies of all sizes will be able to employ digital twins with real-time performance data; create innovative industrial IoT-solutions; leverage actionable insights from analytics at the edge or in the cloud; and tackle the engineering challenges of tomorrow by making visually rich, immersive simulations more accessible.
NVIDIA Omniverse is an AI-enabled, physically simulated and industrial-scale virtual-world engine that enables for the first time full-fidelity live digital twins. NVIDIA AI, used by more than 25,000 companies worldwide, is the intelligence engine of Omniverse in the cloud and autonomous systems at the edge. NVIDIA Omniverse and AI are ideal computation engines to represent the comprehensive digital twin from Siemens Xcelerator.
