Research in Japan shows the way toward tactile and proximity sensing in large soft robots

Isikawa, Japan -- In recent years, robots have become incredibly sophisticated machines capable of performing or assisting humans in all tasks. The days of robots functioning behind a security barrier are long gone, and today we may anticipate robots working alongside people in close contact. While working alongside robots may be very practical in some situations, they should be designed to be safe and pleasant for humans to interact with. For instance, in human-robot interactions (HRIs), robots should be able to react correctly to potential collisions with humans and also respond safely and predictably to intentional physical contact.

One of the best approaches to improve HRIs is to grant robots the ability to sense their environment in multiple ways, such as by touch, sound, and sight. Of these three, tactile sensation is particularly important for robots that are likely to come into physical contact with humans during operation. Although small-scale tactile sensors have seen tremendous progress over the past decade, the development of large-scale tactile sensors has been plagued with challenges. Moreover, most researchers have focused on systems that respond to physical touch and ignore touchless stimuli, such as when an object is in close proximity. To address these issues, a research team led by Associate Professor Van Anh Ho from Japan Advanced Institute of Science and Technology (JAIST) recently developed ProTac—an innovative soft robotic link with tactile and proximity sensing capabilities. As explained in their paper, presented at the IEEE-RAS International Conference on Soft Robotics (ROBOSOFT), the team not only engineered ProTac itself but also pioneered a new simulation and learning framework to effectively prepare the robotic link for use.

But what does a robotic link look like, and what is ProTac good for? In general, robotic links are rigid structural components of a robot that connect two or more joints. For example, robotic links can be seen as various ‘segments’ in a robotic limb. In this study, ProTac is designed as a soft, cylindrical segment for a robotic arm. What makes it remarkable is how the researchers incorporated the tactile and proximity sensing capabilities in a very convenient and space-efficient way.

ProTac has an outer ‘soft magic skin’ that can be slightly deformed by touch without damage. The inside of the skin is patterned with arrays of reflective markers, and fisheye cameras are installed at both ends of the robotic link looking towards these markers. The idea is that, upon physical contact and deformation of the skin, changes in the relative positions of the markers are captured by the cameras and processed to calculate the precise location and intensity of the contact. On top of this, the outer skin is of a functional polymer that can be made entirely transparent by applying an external voltage. It allows the fisheye cameras to image the immediate surroundings of ProTac, providing footage for proximity calculations.   

To more easily train ProTac to make proximity and tactile measurements, the team also developed SimTacLS, an open-source simulation and learning framework based on the SOFA and Gazebo physics engines (see the paper here). This machine learning framework is trained with simulated and experimental data considering the physics of soft contact and the realistic rendering of sensor images. “SimTacLS enabled us to effectively implement tactile perception in robotic links without the high costs of complex experimental setups,” remarks Prof. Ho, “Furthermore, with this framework, users can readily validate sensor designs and learning-based sensing performance before proceeding to actual fabrication and implementation.”

Overall, this work will help pave the way to a world where humans can harmoniously coexist and work alongside robots. Excited by the team’s contribution to this dream, Prof. Ho comments: “We expect the proposed sensing device and framework to bring in ultimate solutions for the design of robots with softness, whole-body and multimodal sensing, and safety control strategies.” It is worth noting that proposed techniques can be extended to other types of robotic systems beyond the robotic manipulator demonstrated in the study, such as mobile and flying robots. Moreover, ProTac or similar robotic links could be used to enable robotic manipulation in cluttered environments or when operating in close vicinity with humans.

Only time will tell how close we’ll be to working with robots in the coming years!

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About Japan Advanced Institute of Science and Technology, Japan

Founded in 1990 in Ishikawa prefecture, the Japan Advanced Institute of Science and Technology (JAIST) was the first independent national graduate school in Japan. Now, after 30 years of steady progress, JAIST has become one of Japan’s top-ranking universities. JAIST counts with multiple satellite campuses and strives to foster capable leaders with a state-of-the-art education system where diversity is key; about 40% of its alumni are international students. The university has a unique style of graduate education based on a carefully designed coursework-oriented curriculum to ensure that its students have a solid foundation on which to carry out cutting-edge research. JAIST also works closely both with local and overseas communities by promoting industry–academia collaborative research.  

About Associate Professor Van Anh Ho from Japan Advanced Institute of Science and Technology, Japan

Dr. Van Anh Ho received a Ph.D. in robotics from Ritsumeikan University, Japan, in 2012 and completed a JSPS Postdoctoral Fellowship in 2013. He joined the Japan Advanced Institute of Science and Technology in 2017 and helped set up the Laboratory on Soft Robotics. His research interests include soft robotics, soft-haptic interaction, tactile sensing, grasping and manipulation, and bio-inspired robots. He has over 60 scientific publications to his name. He received the 2019 IEEE Nagoya Chapter Young Researcher Award and was a Best Paper Finalist at IEEE SII in 2016 and IEEE RoboSoft in 2020.

Funding information:

This study was supported by Japan Science and Technology Agency's Precursory Research for Embryonic Science and Technology (Grant Number: JPMJPR2038).