Category Robotics Classification

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A robotic cat can teach us how real animals move

Image: AlesiaKan/Shutterstock.com

By Mischa Dijkstra, Frontiers science writer / Toyoaki Tanikawa, Department of Mechanical Engineering, Osaka University

In the young discipline of robotics-inspired biology, robots replace experimental animals, allowing researchers to learn about animals under a wider range of conditions than exist in nature or the laboratory.

What is the secret behind the steady but oh-so-elegant way in which cats move? That’s the subject of a study in Frontiers in Neurorobotics by scientists from Osaka University, who built a novel, 47cm-long and 7.6kg-heavy robotic cat. Based on previous research on the gait of real domestic cats, the authors deduced that key to the cats’ sleek movement must lie in a previously unknown reflex circuit, which they call the “reciprocal excitatory circuit between hip and knee extensors”.

According to their hypothesis, this reflex circuit has two essential features. The first is the mechanical unloading of a cat’s ankle extensor muscles, which prompts the transition from the stance to the swing phase. The second is muscle movement within the hip joint, which initiates the next transition, from swing to stance.

Trial-and-error with their robotic cat showed that their hypothesis was correct: even without a central pattern generator, a key feature of most moving robots, the novel reflex circuit gave a steady gait to the ‘robocat’, mimicking the movement of real cats.

The study’s first author, Toyoaki Tanikawa, is a young roboticist from Japan. After graduating from the advanced course in industrial and systems engineering at the National Institute of Technology-Kagawa College in early 2019, Tanikawa entered the MSc program at Osaka University’s Department of Mechanical Engineering, where he has done research on walking robots for the past two years.

Here he explains what first brought him to the field of robotics, how he and his supervisors assistant professor Masuda Youichi and Prof Ishikawa Masato developed the new ‘robocat’, and how mutual inspiration and exchange of knowledge between robotics and biology can benefit both fields.

Toyoaki Tanikawa

Because open access and sharing research is part of Frontiers’ mission, we want to give researchers the voice to express themselves and their research with more creativity and freedom than they otherwise would have in publishing an academic paper.

If you’ve recently published your paper with Frontiers and believe you have a great story to tell, then send an email to press@frontiersin.org with ‘Frontier Scientists’ and your name in the subject line.

What inspired you to become a researcher? Do you have any specific memories that set off a spark?

What made me decide to do the research was the robot competition, called RoboCon, in my school days. When I was a student at Kagawa Tech, I was a member of a team participating in that competition. I developed the circuitry and software for some competition robots, and experienced that the performance of a robot can vary greatly depending on its control.

Since then, I have been interested in what kind of control can maximize the performance of a robot. For this reason, in my master’s course, I conducted research on control inspired by animals that can move adaptively in various environments.

Can you tell us about the research you’re currently working on?

We focused on understanding the mechanisms of animal locomotion by developing quadruped robots that can reproduce the neuromuscular dynamics of animals.

Reproducing control structures of animals in robots has two aims. First, to contribute to the well-known field of biology-inspired robotics, where the structure of a robot is made similar to that of an animal. We hope that our results will thus result in fundamental new technology for realizing robots that move efficiently and flexibly like animals.

Second, we aim to contribute to biology in return. At present, experiments using real animals are strictly controlled and restricted, making it difficult to study the inner workings of living, moving animals. In the young research field of robotics-inspired biology, researchers are trying to understand animals by using robots instead of experimental animals. In the future, as more and more robots replace experimental animals, researchers may be able to investigate animal mechanisms under a wider variety of experimental conditions.

In the future, as more and more robots replace experimental animals, researchers may be able to investigate animal mechanisms under a wider variety of experimental conditions.

Toyoaki Tanikawa

In your opinion, why is your research important?

First, in our new study we contribute to the development of novel scientific methods to reproduce and understand quadrupeds using robots, as described above. Another important result is that we have provided a new hypothesis about the locomotion mechanism of cats.

By exploring reflex circuits that could result in a walking quadruped robot, we arrived at a simple novel reflex circuit, which we have named ‘reciprocal excitatory circuit between hip and knee extensors’. By simply reproducing the reciprocal circuit in each leg, the robot generated steady walking motions. We also show that the robot’s gait becomes unstable when the reciprocal circuit is cut off, and that the reciprocal excitatory circuit produced a phenomenon known to occur in cats, called ‘prolongation of the stance phase’. This suggests that the reciprocal excitatory circuit is an important component of the cat’s neural circuit.

Are there any common misconceptions about this area of research? How would you address them?

Robotics is often thought of as a technology that is only for building better robots. However, if used in a different way, robotics can be a very useful scientific tool for reproducing and understanding dynamical systems with complex interactions, such as animals. Of course, not all phenomena discovered in the robot will be observed in animals, but the cycle of discovering new phenomena can be accelerated by providing new hypotheses to biology based on findings from the robot.

What are some of the areas of research you’d like to see tackled in the years ahead?

I graduated from the master’s course this spring and got a job at a company. If I have a chance to do my research in the future, I would like to work on the motion control of robots, which is a further development of our results.

How has open science benefited the reach and impact of your research?

Papers submitted to open access journals have fewer copyright issues. Therefore, I can use various means such as images and videos to advertise the results of my research to the public. Also, since I am leaving the university this spring, being able to read academic papers for free will be a great advantage.

Read Tanikawa et al’s study in Frontiers in Neurorobotics: A Reciprocal Excitatory Reflex Between Extensors Reproduces the Prolongation of Stance Phase in Walking Cats: Analysis on a Robotic Platform.

This article was initially published on the Frontiers blog.

A tactile sensing mechanism for soft robotic fingers

In recent years, numerous roboticists worldwide have been trying to develop robotic systems that can artificially replicate the human sense of touch. In addition, they have been trying to create increasingly realistic and advanced bionic limbs and humanoid robots, using soft materials instead of rigid structures.

#IROS2020 Real Roboticist focus series #1: Davide Scaramuzza (Drones & Magic)

Are you curious about the people behind the robots? The series ‘Real Roboticist’, produced by the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), shows the people at the forefront of robotics research from a more personal perspective. How did they become roboticists? What made them proud and what challenges did they face? What advice would they give to their younger self? What does a typical day look like? And where do they see the future of robotics? In case you missed it during the On-Demand conference, no worries! IEEE has recently made their original series public, and every Sunday we’ll bring you an interview with a real roboticist for you to get inspired.

This week is the turn of Davide Scaramuzza, Professor and Director of the Robotics and Perception Group at the University of Zürich. In his talk, Davide explains his journey from Electronics Engineering to leading a top robotics vision research group developing a promising technology: event cameras. He’ll also speak about the challenges he faced along the way, and even how he combines the robotics research with another of his passions, magic. Curious about where the magic happens? Davide also takes you around his research lab during the interview. Let the magic happen!

r/Robotics showcase

The first Reddit Robotics Showcase will take place online this weekend (31st July – 1 August). Multitude of projects underway in the r/robotics reddit community will be showcased. There will be nearly 30 presentations from members of the r/robotics community, ranging from hobbyists, professionals, academics, industrial, students, etc. across four different categories: simulation, mobile robots, manipulation, and legged robots. The showcase will be livestreamed via the Reddit Robotics Showcase YouTube channel, and you will be able to pose questions to the participants.

Keynote Speakers

Saturday, 31st of July
Simulation: Brian Gerkey – Open Robotics – 10:00 EDT (15:00 BST, 23:00 JST)
Mobile Robots: Mark Emerton – UKRI – 14:00 EDT (19:00 BST, 03:00 JST)

Sunday, 1st of August
Manipulation: Rich Walker – Shadow Robot Company – 10:00 EDT (15:00 BST, 23:00 JST)
Legged Robots: Shamel Fahmi – Italian Institute of Technology – 14:00 EDT (19:00 BST, 03:00 JST)

For more information and the full programme, please visit the website.

A new taxonomy to characterize human grasp types in videos

Over the past few decades, roboticists and computer scientists have developed a variety of data-based techniques for teaching robots how to complete different tasks. To achieve satisfactory results, however, these techniques should be trained on reliable and large datasets, preferably labeled with information related to the task they are learning to complete.

#IROS2020 Plenary and Keynote talks focus series #1: Yukie Nagai & Danica Kragic

Would you like to stay up to date with the latest robotics & AI research from top roboticists? The IEEE/RSJ IROS2020 (International Conference on Intelligent Robots and Systems) recently released their Plenary and Keynote talks in the IEEE RAS YouTube channel. We’re starting a new focus series with all their talks. This week, we’re featuring Professor Yukie Nagai (University of Tokyo), talking about cognitive development in humans and robots, and Professor Danica Kragic (KTH Royal Institute of Technology), talking about the impact of robotics and AI in the fashion industry.

Prof. Yukie Nagai – Cognitive Development in Humans and Robots: New Insights into Intelligence

Abstract: Computational modeling of cognitive development has the potential to uncover the underlying mechanism of human intelligence as well as to design intelligent robots. We have been investigating whether a unified theory accounts for cognitive development and what computational framework embodies such a theory. This talk introduces a neuroscientific theory called predictive coding and shows how robots as well as humans acquire cognitive abilities using predictive processing neural networks. A key idea is that the brain works as a predictive machine; that is, the brain tries to minimize prediction errors by updating the internal model and/or by acting on the environment. Our robot experiments demonstrate that the process of minimizing prediction errors leads to continuous development from non-social to social cognitive abilities. Internal models acquired through their own sensorimotor experiences enable robots to interact with others by inferring their internal state. Our experiments inducing atypicality in predictive processing also explains why and how developmental disorders appear in social cognition. I discuss new insights into human and robot intelligence obtained from these studies.

Bio: Yukie Nagai is a Project Professor at the International Research Center for Neurointelligence, the University of Tokyo. She received her Ph.D. in Engineering from Osaka University in 2004 and worked at the National Institute of Information and Communications Technology, Bielefeld University, and Osaka University. Since 2019, she leads Cognitive Developmental Robotics Lab at the University of Tokyo. Her research interests include cognitive developmental robotics, computational neuroscience, and assistive technologies for developmental disorders. Her research achievements have been widely reported in the media as novel techniques to understand and support human development. She also serves as the research director of JST CREST Cognitive Mirroring.

Prof. Danica Kragic – Robotics and Artificial Intelligence Impacts on the Fashion Industry

Abstract: This talk will overview how robotics and artificial intelligence can impact fashion industry. What can we do to make fashion industry more sustainable and what are the most difficult parts in this industry to automate? Concrete examples of research problems in terms of perception, manipulation of deformable materials and planning will be discussed in this context.

Bio: Danica Kragic is a Professor at the School of Computer Science and Communication at the Royal Institute of Technology, KTH. She received MSc in Mechanical Engineering from the Technical University of Rijeka, Croatia in 1995 and PhD in Computer Science from KTH in 2001. She has been a visiting researcher at Columbia University, Johns Hopkins University and INRIA Rennes. She is the Director of the Centre for Autonomous Systems. Danica received the 2007 IEEE Robotics and Automation Society Early Academic Career Award. She is a member of the Royal Swedish Academy of Sciences, Royal Swedish Academy of Engineering Sciences and Young Academy of Sweden. She holds a Honorary Doctorate from the Lappeenranta University of Technology. Her research is in the area of robotics, computer vision and machine learning. She received ERC Starting and Advanced Grant. Her research is supported by the EU, Knut and Alice Wallenberg Foundation, Swedish Foundation for Strategic Research and Swedish Research Council. She is an IEEE Fellow.

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