UC Berkeley Professor and TerraSwarm PI receives IEEE Fellow distinction

On November 28th, the Institute of Electrical and Electronics Engineers (IEEE) named Terraswarm PI and UC Berkeley professor Sanjit Seshia as a newly elevated Fellow, a prestigious honor within the technical community. Professor Seshia was selected for contributions to formal methods for inductive synthesis and algorithmic verification.

The IEEE Fellow distinction is reserved for select members who have a remarkable record of accomplishments in any of the IEEE fields of interest. More about this notable distinction in INDIAWEST.

TerraSwarm PI and Professor at the University of Washington speaks for Apple at NIPS conference

While simultaneously an Associate Professor of Machine Learning at the Computer Science and Engineering Department of the University of Washington and a TerraSwarm PI, Carlos Guestrin addressed attendees at the 2017 NIPS conference as Apple's Director of Machine Learning. Prof. Guestrin spoke about the powerful computer systems and large datasets available to machine-learning engineers who join Apple. Winning applause from his audience, he also announced that Apple is open sourcing software to help application developers use machine learning first developed in his own startup Turu, which was acquired by Apple last summer.

To see more, go to Patently Apple as well as an article about Apple's revelation of more of its self-driving technology at the same conference that appears in Wired.

Can driverless cars be safe? Penn State Professor and TerraSwarm PI Rahul Mangharam and team are working on it

Much attention in the area of autonomous cars is focused in Pittsburgh, Pennsylvania, where Carnegie Mellon University has positioned itself as a leader in this field. The University of Pennsylvania, along with CMU, is a key player in Mobility21, a five-year, federally funded $14 million program to investigate transportation technology, including autonomous vehicles. Colleagues at at CMU are experimenting with their own autonomous car while scientists at Penn work in a lab driving cars virtually in all types of weather and lighting to test how well the software adapts to the changes it would face in the real world.

Rahul Mangharam, associate professor of Electrical and Systems Engineering at the University of Pennsylvania, is leading a team of six researchers in pursuit of what they describe as a "driver's license test" for self-driving cars. The test involves a rigorous use of mathematical diagnostics and simulated reality to determine the safety of autonomous vehicles before they ever hit the road.

All in service of rating robot drivers, white boards covered in complex equations, shelves full of makeshift toy cars and computer screens displaying video games comprise the environment of the Penn lab. Penn scientists run the autonomous driving software, called Computer Aided Design for Safe Autonomous Vehicles, through both mathematical diagnostics and the virtual reality test drives on Grand Theft Auto to see when the system fails.

“You can never have 100 percent safety,” Mangharam said. “You can design a system that would not be at fault intentionally.” As much as he believes in autonomous technology, Mangharam is concerned about our society's tendency to neglect regulatory oversight as we embrace a new toy.

See article at The Inquirer

CMU to participate in LoRaWAN Academy curriculum

The LoRaWAN Academy announced the participation of the College of Engineering at Carnegie Mellon University in the LoRaWAN Academy curriculum yesterday, where CMU had developed its own network, OpenChirp, an LPWAN network.

“Connecting sensors is often the most expensive and challenging part of a deployment especially when they are located in remote areas where data needs to travel long distances. By implementing battery-operated, low-powered LoRaWAN-based devices and the LoRaWAN protocol, OpenChirp demonstrates that it is feasible to scale low-powered sensing devices for use across large areas, like campuses, manufacturing plants or even cities,” said Anthony Rowe, an associate professor of electrical and computer engineering, who leads the OpenChirp project at CMU. “At Carnegie Mellon, students are using OpenChirp to develop IoT applications including smart grid demand / response, air quality sensing, and a campus asset-tracking system.”

Carnegie Mellon’s work is a prime example of the LoRaWAN-based projects that students can develop with LoRa Technology and the LoRaWAN open protocol. See Market Insider.

UC Berkeley Professor and TerraSwarm PI Pieter Abbeel heads new startup of AI hotshots

Professor Peter Abbeel's research at UC Berkeley's Robot Lab had been working on adaptive learning through demonstration, initially with the famous towel-folding performed by a robot and the robotic knot-tying from 2013. This week, Abbeel and several colleagues announced a new startup (with US $7 million in seed funding) called Embodied Intelligence which will “enable industrial robot arms to perceive and act like humans instead of just strictly following pre-programmed trajectories.”

The new project draws on the groundwork laid by BRETT, a robot that represented a deep reinforcement learning breakthrough for UC Berkeley in 2015. The acronym, believe it or not, stands for Berkeley Robot for the Elimination of Tedious Tasks.

“Right now, if you want to set up a robot, you program that robot to do what you want it to do, which takes a lot of time and a lot of expertise,” said Abeel. “With our advances in machine learning, we can write a piece of software once — machine learning code that enables the robot to learn — and then when the robot needs to be equipped with a new skill, we simply provide new data.”

The new start-up plans to make robots more skillful and quicker to learn, which could have an enormous impact on manufacturing.

“The goal is to bring the cutting-edge research to robotics and manufacturing,” Abbeel says. He says the techniques his company is developing will enable robots to do a range of things that are currently too time-consuming to be programmed in.

See articles in IEEE Spectrum, Electronics 360 and MIT Technology Review for more information.

Caltech Professor and TerraSwarm PI recipient of NIH BRAINS Grant

PASADENA NOW reports on NIH Grants awarded to 5 CalTech faculty for 3 projects aimed at identifying all cell types in the mouse brain, understanding how the brain heals itself after disease or injury, and understanding the neural circuits of behavior.

As one of the 5 Caltech researchers to receive grants from the National Institutes of Health's Brains Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative, Professor Richard Murray, along with Professor Michael Dickinson, will concentrate their research on the NIH project ""A brain circuit program for understanding the sensorimotor basis of behavior".

Professor Murray, a co-principal investigator, has collaborated extensively with Dickinson on modeling and analyzing the biological systems of insect flight control.

“The collective expertise of these research teams spans the entire nervous system, from the sensory periphery to the motor periphery, and it includes experts in every experimental technique we require—molecular genetics, electrophysiology, optical imaging, biomechanics, quantitative behavioral analysis, control theory, and dynamic network theory,” says Murray. “We will exploit mathematical approaches—control theory and dynamic network theory in particular—that are well suited to model feedback and the flow of information through and among different processing stages in the brain.”

Director of DCIST at University of Pennsylvania and TerraSwarm PI Vijay Kumar receives $27M grant from Army to develop robot teams

The United States Army Research Laboratory (ARL) has awarded Penn Engineering a five-year, $27 million grant to develop new methods of creating autonomous, intelligent and resilient teams of robots. The teams, comprised of multiple types of robots and sensors with varying abilities, are designed to assist humans in a broad range of operations in dynamically changing, harsh and challenging environments. These would include search and rescue of hostages, information gathering after terrorist attacks or natural disasters as well as humanitarian missions.

“We want to have teams of robots that know how to work together, but can figure out how to keep working even if some of their teammates crash or fail, if GPS signal is unavailable, or if cloud services are disrupted,” said Vijay Kumar, director of the DCIST program. “This means designing networks with loose, flexible connections that can change on the fly. That way, a single event can’t bring down the entire network. More importantly, we want them to learn to perform tasks they may have never performed and work alongside humans that they may never have worked with.”

The award is part of ARL's Distributed and Collaborative Intelligent Systems and Technology (DCIST) Collaborative Research Alliance, which Penn Engineering will lead.

“The technology we’re working will better allow humans to respond by projecting their intelligence without directly coming in harm’s way,” Kumar said.

See Electronics 360 and Georgia Tech NEWS CENTER for more information.