Robots Made Out of Branches Use Deep Learning to Walk

Researchers used deep reinforcement learning to teach these strange robots how to move

2 min read
Robot Made Out of Branches Uses Deep Learning to Walk
Researchers from Preferred Networks built robots out of unusual materials like tree branches and used deep reinforcement learning to develop locomotion algorithms for them.
Photo: Azumi Maekawa

Designing robots is a finicky process, requiring an exhaustive amount of thought and care. It’s usually necessary to have a very clear idea of what you want your robot to do and how you want it to do it, and then you build a prototype, discover everything that’s wrong with it, build something different and better, and repeat until you run out of time and/or money.

But robots don’t necessarily have to be this complicated, as long as your expectations for what they should be able to do are correspondingly low. In a paper presented at a NeurIPS workshop last December, a group of researchers from Preferred Networks experimented with building mobile robots out of a couple of generic servos plus stuff you can find on the ground, like tree branches. 

These robots figure out how to walk in simulation first, through deep reinforcement learning. The way this is implemented in the paper is by picking up some sticks, weighing and 3D scanning them, simulating the entire robot, and then rewarding gaits that result in the farthest movement. There’s also some hand-tuning involved to avoid behaviors that might (for example) “cause stress and wear in the real robot.” 

Overall, this is maybe not the kind of strategy that you’d be able to use for most applications, but we can speculate about how robots like these could become a little bit more practical at some point. The idea of being able to construct a mobile robot out of whatever is lying around (plus some servos and maybe a sensor or two) is a compelling one, and it seems like you could develop a gait from scratch on the physical robot using trial and error and feedback from some basic sensors, since we’ve seen similar things done on other robotic platforms.

Mobile robot made of tree branches and powered by AI walking algorithmsThe robot is controlled by an Arduino Mega and powered by Kondo KRS-2572HV servo motors with a separate driver and power supply.Image: Preferred Networks

Found materials robots like these are not likely to be as capable as traditional robotic designs, so they’d likely only be useful under special circumstances. Not having to worry about transporting structural materials would be nice, as would being able to create a variety of designs as necessary using one generalized hardware set. And building a robot out of locally available materials means that anything you put together will be really easy to fix, even if you do have to teach it to move all over again.

Improvised Robotic Design With Found Objects,” by Azumi Maekawa, Ayaka Kume, Hironori Yoshida, Jun Hatori, Jason Naradowsky, and Shunta Saito, from Preferred Networks, Inc., was presented at the Workshop on Machine Learning for Creativity and Design at NeurIPS 2018.

[ Azumi Maekawa ] via [ HY-MA ]

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How Robots Can Help Us Act and Feel Younger

Toyota’s Gill Pratt on enhancing independence in old age

10 min read
An illustration of a woman making a salad with robotic arms around her holding vegetables and other salad ingredients.
Dan Page
Blue

By 2050, the global population aged 65 or more will be nearly double what it is today. The number of people over the age of 80 will triple, approaching half a billion. Supporting an aging population is a worldwide concern, but this demographic shift is especially pronounced in Japan, where more than a third of Japanese will be 65 or older by midcentury.

Toyota Research Institute (TRI), which was established by Toyota Motor Corp. in 2015 to explore autonomous cars, robotics, and “human amplification technologies,” has also been focusing a significant portion of its research on ways to help older people maintain their health, happiness, and independence as long as possible. While an important goal in itself, improving self-sufficiency for the elderly also reduces the amount of support they need from society more broadly. And without technological help, sustaining this population in an effective and dignified manner will grow increasingly difficult—first in Japan, but globally soon after.

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