Paolo Pirjanian, Niklas Karlsson, Luis Goncalves and Enrico Di Bernardo
One difficult problem in robotics is localization: the ability of a mobile robot to determine its position in the environment. Roboticists around the globe have been working to…
Abstract
One difficult problem in robotics is localization: the ability of a mobile robot to determine its position in the environment. Roboticists around the globe have been working to find a solution to localization for more than 20 years; however, only in the past 4‐5 years we have seen some promising results. In this work, we describe a first‐of‐a‐kind, breakthrough technology for localization that requires only one low‐cost camera (less than 50USD) and odometry to provide localization. Because of its low‐cost and robust performance in realistic environments, this technology is particularly well‐suited for use in consumer and commercial applications.
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PhD/inventor builds consumer robot start-up company based on low-cost, groundbreaking visual simultaneous localization and mapping (vSLAM) visual sensors and NorthStar® navigation…
Abstract
Purpose
PhD/inventor builds consumer robot start-up company based on low-cost, groundbreaking visual simultaneous localization and mapping (vSLAM) visual sensors and NorthStar® navigation technologies that sells for nearly $75 million dollars 12 years later. The following article is a “Q&A interview” conducted by Joanne Pransky of Industrial Robot Journal as a method to impart the combined technological, business, and personal experience of a prominent, robotic industry engineer-turned entrepreneur regarding the evolution, commercialization, and challenges of bringing a technological invention to market. The paper aims to discuss these issues.
Design/methodology/approach
This interview was with Dr Paolo Pirjanian, CTO of iRobot Corporation. Dr Pirjanian previously served as both CTO and CEO of Evolution Robotics. Dr Pirjanian received his PhD degree from Aalborg University, Denmark. He has received several honors and awards including the IEEE Robotics and Automation Society Early Career Award in 2004 and the Technical Leadership Award from JPL/NASA. Dr Pirjanian holds 67 patents.
Findings
The challenges and solutions of transferring technological innovations into an affordable consumer product are presented. The resulting pioneering technologies and approximate 37 patents around vSLAM and NorthStar® were incorporated into Evolution's flagship consumer product, Mint floor cleaning robot. In October 2012, iRobot Corp acquired Evolution for $74 million in an effort to complement their own products and technologies.
Originality/value
A robot scientist, in his roles as the CTO and CEO of a robot company, uses a paradigm shift in vision and pattern recognition to build an affordable consumer product and successful company.
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The following paper is a “Q&A interview” conducted by Joanne Pransky of Industrial Robot Journal as a method to impart the combined technological, business and personal experience…
Abstract
Purpose
The following paper is a “Q&A interview” conducted by Joanne Pransky of Industrial Robot Journal as a method to impart the combined technological, business and personal experience of a prominent, robotic industry PhD and innovator regarding her pioneering efforts and the challenges of bringing a technological invention to market. This paper aims to discuss these issues.
Design/methodology/approach
The interviewee is Dr Maja Matarić, Chan Soon-Shiong Distinguished Professor in the Computer Science Department, Neuroscience Program, and the Department of Pediatrics at the University of Southern California, founding director of the USC Robotics and Autonomous Systems Center (RASC), co-director of the USC Robotics Research Lab and Vice Dean for Research in the USC Viterbi School of Engineering. In this interview, Matarić shares her personal and business perspectives on socially assistive robotics.
Findings
Matarić received her PhD in Computer Science and Artificial Intelligence from MIT in 1994, MS in Computer Science from MIT in 1990 and BS in Computer Science from the University of Kansas in 1987. Inspired by the vast potential for affordable human-centered technologies, she went on to found and direct the Interaction Lab, initially at Brandeis University and then at the University of Southern California. Her lab works on developing human–robot non-physical interaction algorithms for supporting desirable behavior change; she has worked with a variety of beneficiary user populations, including children with autism, elderly with Alzheimer’s, stroke survivors and teens at risk for Type 2 diabetes, among others.
Originality/value
Matarić is a pioneer of the field of socially assistive robotics (SAR) with the goal of improving user health and wellness, communication, learning and autonomy. SAR uses interdisciplinary methods from computer science and engineering as well as cognitive science, social science and human studies evaluation, to endow robots with the ability to assist in mitigating critical societal problems that require sustained personalized support to supplement the efforts of parents, caregivers, clinicians and educators. Matarić is a Fellow of the American Association for the Advancement of Science (AAAS), Fellow of the IEEE and AAAI, recipient of the Presidential Awards for Excellence in Science, Mathematics & Engineering Mentoring (PAESMEM), the Anita Borg Institute Women of Vision Award for Innovation, Okawa Foundation Award, NSF Career Award, the MIT TR35 Innovation Award, the IEEE Robotics and Automation Society Early Career Award and has received many other awards and honors. She was featured in the science documentary movie “Me & Isaac Newton”, in The New Yorker (“Robots that Care” by Jerome Groopman, 2009), Popular Science (“The New Face of Autism Therapy”, 2010), the IEEE Spectrum (“Caregiver Robots”, 2010), and is one of the LA Times Magazine 2010 Visionaries. Matarić is the author of a popular introductory robotics textbook, “The Robotics Primer” (MIT Press 2007), an associate editor of three major journals and has published extensively.
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Gerard A.J. Pounder, Ruel L.A. Ellis and Gerardo Fernandez-Lopez
This paper aims to introduce the cognitive function synthesis (CFS) conceptual framework to artificial general intelligence. CFS posits that at the “core” of intelligence in…
Abstract
Purpose
This paper aims to introduce the cognitive function synthesis (CFS) conceptual framework to artificial general intelligence. CFS posits that at the “core” of intelligence in hybrid architectures, “interdependent” cognitive functions are synthesised through the interaction of various associative memory (AM)-based systems. This synthesis could form an interface layer between deliberative/symbolic and reactive/sub-symbolic layers in hybrid cognitive architectures.
Design/methodology/approach
A CFS conceptual framework, specifying an arrangement of AMs, was presented. The framework was executed using sparse distributed memory. Experiments were performed to investigate CFS autonomous extraction, consciousness and imagination.
Findings
Autonomous extraction was achieved using data from a Wi-Fi camera with the CFS auto-associative AM handling “Sensor Data”. However, noise reduction degraded the extracted image. An environment, simulated in V-REP 3.3.1, was used to investigate consciousness and imagination. CFS displayed consciousness by successfully tracking/anticipating the object position with over 90 per cent congruence. CFS imagination was seen by its predicting two time steps into the future.
Originality/value
Preliminary results demonstrate the plausibility of CFS claims for autonomous extraction, consciousness and imagination.