Beep Trains Orlando First Responders on Autonomous Vehicle Technology

ORLANDO, Fla. — Florida-based autonomous mobility solutions company Beep announced this week it is conducting an enhanced training program for Orlando first responders designed to familiarize them with autonomous technology and train them on appropriate actions to take if the vehicles are present on a scene. Led by experts from NAVYA’s Michigan assembly plant, the training, held earlier this week, consisted of familiarizing first responders with all the systems aboard NAVYA’s AUTONOM shuttle.

Training reviewed how to interact with the vehicle in emergency situations and include a hands-on session on how to operate the vehicle, which is expected to become Central Florida’s first autonomous shuttle this summer.

“As first responders, our knowledge and skills need to keep evolving with the automotive technology that people have access to now and in the future,” said Orlando Fire Chief Richard Wales. “We are very pleased to be participating in this training exercise and we look forward to learning the protocol for operating and addressing any situations with these vehicles should they be present at an incident.”

“The transportation industry is evolving dramatically right now, with more autonomous technology than ever making its way onto our roads,” said Joe Moye, Beep’s CEO. “Our commitment and responsibility for making sure people are moving around safely on our shuttles is our priority, and this training ensures that first responders are familiar with the vehicles and can confidently interact with them should the need arise.”

Beep has an exclusive dealer arrangement for the state of Florida, with autonomous vehicle manufacturer NAVYA, maker of the AUTONOM shuttle, which underpins Beep’s services. The electric shuttles are fully autonomous, driverless, and utilize advanced guidance and detection systems to interact in real time with their environment.

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“NAVYA has a perfect safety record according to the National Highway Traffic Safety Administration’s (NHTSA) Automated Driving Systems Voluntary Safety Self-Assessment (VSSA) Disclosure Index,” continued Moye. “Their advanced technology and focus on safety are why Beep chose NAVYA as a partner, and this training program is a further indication of our relentless focus on the safety of our vehicles and the passengers they transport.”

Currently, Beep and Lake Nona are pursuing approvals with NHTSA and the Department of Transportation (DOT) for proposed autonomous shuttle routes throughout Lake Nona. Lake Nona will start with two shuttles that can hold up to 15 people each and will travel on fixed routes within the community at speeds up to 16 mph. Each shuttle will have a dedicated attendant on board.

“We applaud Beep, NAVYA, and the Orlando Fire Department for taking the initiative to begin this training program and ensure our first responders are prepared to engage with latest autonomous technology,” said Juan Santos, Lake Nona’s VP of Brand Experience. “As we get closer to having the shuttles operational in Lake Nona this summer, we also plan to host additional informational events geared toward riders.”
Beep Trains Orlando First Responders on Autonomous Vehicle Technology

Almost 80% of AI and ML Projects Have Stalled, Survey Says

AUSTIN, Texas – Nearly eight out of 10 enterprise organizations currently engaged in artificial intelligence or machine learning projects have reported stalled progress, according to a survey released today by Alegion and Dimensional Research.

Furthermore, 96% of the companies survey said they have run into problems with data quality, data labeling required to train AI, and building model conference. The new report, “Artificial Intelligence and Machine Learning Obstructed by Data Issues”, indicated that data issues are causing enterprises to quickly burn through AI project budgets and creating project hurdles.

Nathaniel Gates, Alegion CEO

“The single largest obstacle to implementing machine learning models into production is the volume and quality of the training data,” said Nathaniel Gates, CEO and co-founder of Alegion, which develops a training data platform for AI and ML. “This research reinforces our own experience, that data science teams new to building ROI-driven systems try to tackle training data preparation in house, and get overwhelmed.”

Gates added that many companies encounter challenges early in the process, especially around accurately and efficiently labeling and annotating enough data to train their algorithms. “We believe that as enterprise data science teams gain more experience with machine learning projects, they’ll be more likely to offload activities such as data labeling, model validation and scoring, and in doing so speed their path to model deployment.”
New concept, harder than thought
While large businesses with more than 100,000 employees are the most likely to have an AI strategy, only 50% of them currently have one, according to MIT Sloan Management Review. Alegion said in its survey, AI is still a new concept:

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70% said their first AI/ML investment was within the last 24 months.
More than half of enterprises said they have undertaken fewer than four AI and ML projects.
Only half of the enterprises have released their projects into production.

Additional responses indicated even more challenges within their projects:

78% of AI/ML projects stall at some stage before deployment, with one-third stalling at the proof of concept stage.
81% said the process of training AI with data was more difficult than they expected.
76% attempt to label and annotate training data on their own.
63% try to build their own labeling and annotation automation technology.
71% said they ultimately outsourced their draining data and other ML project activities.

When asked the types of problems that they’ve experienced with AI training data:

66% said they had bias or errors in the data
51% said they didn’t have enough data
50% said data was not in a usable form
28% said they didn’t have the people needed to label the data

The electronic survey was conducted by Dimensional Research of 227 participants, representing five continents and 20 industries. Participants represented enterprise data scientists, other AI technologists and business stakeholders involved in active AI and ML projects.
Almost 80% of AI and ML Projects Have Stalled, Survey Says

Georgia Tech Team Wins Mobile Manipulation Challenge at ICRA 2019

MONTREAL – A team from the Georgia Institute of Technology was named winner of the FetchIt! Mobile Manipulation Challenge, held over the past three days at the International Conference on Robotics and Automation. For successfully assembling three kits in 39 minutes, the team earned a prize package that included a Fetch Mobile Manipulation Research Robot – a $100,000 value – along with other prizes from co-sponsors.

The competition was designed to advance the state of technology for applying mobile manipulators, in which robotic arms are fitted onto autonomous mobile robots, for use in manufacturing and related applications. Some industry watchers say that mobile manipulation is one of the “holy grail” in robotics, in which a single robot can grab and object from a shelf or bin, and then deliver it on a mobile platform.
Tasks across manufacturing
Four research teams competed in the event, in which teams were asked to use a Fetch Robotics Mobile Manipulator robot to navigate to stations in a work cell, pick up items with the arm, insert them into a machining tool, place the machined items into kits, and then transport the finished kit to an inspection station and drop-off location. Fetch Robotics, which was the primary sponsor of the challenge, said this was “the first competition that encompasses the full range of activities that are commonly found in manufacturing environments.”

Team DeRAILers from the Georgia Institute of Technology won the FetchIt! Mobile Manipulation Challenge. Image: Fetch Robotics

Teams in the challenge included:

Team Columbia: Columbia University, led by Professor Peter K. Allen, PhD, and Neil Chen
Team DeRAILers: The Georgia Institute of Technology, led by Associate Professor Sonia Chernova, Ph.D., and David Kent
Team RoboHawks: The University of Massachusetts Lowell, led by Professor Holly Yanco, Ph.D., Assistant Professor Reza Ahmadzadeh, Ph.D., and Zhao Han
Team Fido: Independent competitors, Thomas Butterworth and Ben Jarvhi

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“I’d like to congratulate all the teams for their accomplishments during the course of this challenge,” said Russell Toris, Director of Robotics at Fetch Robotics. “When setting out to create this challenge, we knew we wanted to keep it grounded to a real-word scenario. Interacting with machinery that is designed to be used by humans is no easy task. Piece-picking, kitting, and countless other tasks are going to require state-of-the-art perception, motion planning, navigation, and safety all seamlessly working together. The teams’ performance this week indicate that they represent some of the world’s leading experts in these skills.”

“We’re very excited to have won the FetchIt! challenge,” said Georgia Tech’s Sonia Chernova. “It has allowed us to validate our research code in a complex domain. We can’t wait to continue our work with our newest Fetch robot.”

Added Holly Yanco from UMass Lowell: “Everyone from Fetch has been helpful and very encouraging. This has been an amazing experience and the tasks used for the competition form a great basis for our ONR MURI research.”

In addition to the Fetch Robot, the Georgia Tech team was awarded a MRS1000 4-layer LiDAR sensor (provided by sponsors SICK and EandM), along with 7,000 “Schunk Bucks” by sponsor Schunk. The UMass Lowell team, which placed second, was awarded the MRS1000, a TiM561 LiDAR laser scanner, and 5,000 Schunk Bucks. All the other teams were given the TiM561 laser scanner as well.
Georgia Tech Team Wins Mobile Manipulation Challenge at ICRA 2019

Carnegie Mellon, Pitt to Create Autonomous Robotic Trauma Care System

PITTSBURGH—The University of Pittsburgh School of Medicine and Carnegie Mellon University each have been awarded four-year contracts totaling more than $7.2 million from the U.S. Department of Defense to create an autonomous trauma care system that fits in a backpack and can treat and stabilize soldiers injured in remote locations.

The goal of TRAuma Care in a Rucksack: TRACIR is to develop artificial intelligence (AI) technologies enabling medical interventions that extend the “golden hour” for treating combat casualties and ensure an injured person’s survival for long medical evacuations.

A multidisciplinary team of Pitt researchers and clinicians from emergency medicine, surgery, critical care and pulmonary fields will provide real-world trauma data and medical algorithms that CMU roboticists and computer scientists will incorporate in the creation of a hard and soft robotic suit, into which an injured person can be placed. Monitors embedded in the suit will assess the injury, and AI algorithms will guide the appropriate critical care interventions and robotically apply stabilizing treatments, such as intravenous fluids and medications.

Ron Poropatich M.D., Pitt.

Ron Poropatich, M.D., retired U.S. Army colonel, director of Pitt’s Center for Military Medicine Research and professor in Pitt’s Division of Pulmonary, Allergy and Critical Care Medicine, is overall principal investigator on the $3.71 million Pitt contract, with Michael R. Pinsky, M.D., professor in Pitt’s Department of Critical Care Medicine, as its scientific principal investigator. Artur Dubrawski, a research professor in CMU’s Robotics Institute, is principal investigator on the $3.5 million CMU contract.

“Battlefields are becoming increasingly remote, making medical evacuations more difficult,” Poropatich said. “By fusing data captured from multiple sensors and applying machine learning, we are developing more predictive cardio-pulmonary resuscitation opportunities, which hopefully will conserve an injured soldier’s strength. Our goal with TRACIR is to treat and stabilize soldiers in the battlefield, even during periods of prolonged field care, when evacuation is not possible.”
Baby steps on developing robot medics
Much technology still needs to be developed to enable robots to reliably and safely perform tasks, such as inserting IV needles or placing a chest tube in the field, Dubrawski said. Initially, the research will be a series of baby steps demonstrating the practicality of individual components the system will eventually require.

Artur Dubrawski, Carnegie Mellon University.

“Everybody has a slightly different vision of what the final system will look like,” Dubrawski added. “But we see this as being an autonomous or nearly autonomous system — a backpack containing an inflatable vest or perhaps a collapsed stretcher that you might toss toward a wounded soldier. It would then open up, inflate, position itself and begin stabilizing the patient. Whatever human assistance it might need could be provided by someone without medical training.”

With a digital library of detailed physiologic data collected from more than 5,000 UPMC trauma patients, Pinsky and Dubrawski previously created algorithms that could allow a computer program to learn the signals that an injured patient’s health is deteriorating before damage is irreversible and tell the robotic system to administer the best treatments and therapies to save that person’s life.

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“Pittsburgh has the three components you need for a project like this — world-class expertise in critical care medicine, artificial intelligence and robotics,” Dubrawski said. “That’s why Pittsburgh is unique and is the one place for this project.”
Uses beyond the military
While the project’s immediate goal is to carry forward the U.S. military’s principle of “leave no man behind,” and treat soldiers on the battlefield, there are numerous potential civilian applications, said Poropatich.

“TRACIR could be deployed by drone to hikers or mountain climbers injured in the wilderness; it could be used by people in submarines or boats; it could give trauma care capabilities to rural health clinics or be used by aid workers responding to natural disasters,” he said. “And, someday, it could even be used by astronauts on Mars.”

In addition to Dubrawski, CMU researchers on this project include robotics faculty members Howie Choset, Chris Atkeson, John Galeotti and Herman Herman, director of CMU’s National Robotics Engineering Center.
Carnegie Mellon, Pitt to Create Autonomous Robotic Trauma Care System