即興で難易度の高い地形にも対応する「転ばないロボット」を研究者たちが開発
今回は「即興で難易度の高い地形にも対応する「転ばないロボット」を研究者たちが開発」についてご紹介します。
関連ワード (Carnegie Mellon University、Facebook AI、UC Berkeley等) についても参考にしながら、ぜひ本記事について議論していってくださいね。
本記事は、TechCrunch様で掲載されている内容を参考にしておりますので、より詳しく内容を知りたい方は、ページ下の元記事リンクより参照ください。
ロボットというものは即興が苦手だ。いつもと違う路面や障害物に遭遇すると、突然停止したり、激しく転倒したりする。しかし研究者たちは、どんな地形にもリアルタイムで対応し、砂や岩、階段などで路面が急に変化しても、その場で直ちに歩幅を変えて走り続けることができるロボットの新しい動作モデルを開発した。
ロボットの動きは正確でさまざまな用途に対応でき、段差を登ったり崩れた場所を渡ったりすることを「学習」することができるが、これらの行動は個々の訓練されたスキルに近いもので、ロボットはそれらを切り替えて行っている。また、Boston Dynamics(ボストン・ダイナミクス)が開発した「Spot(スポット)」のようなロボットは、押したり蹴ったりしても跳ね返せることで有名だが、これはシステムが物理的な異常を修正しながら、歩行における変わらない方針を追求しているに過ぎない。対応能力を備えた動作モデルもいくつか開発されているが、非常に特殊なもの(例えば、このモデルは本物の昆虫の動きに基づいている)だったり、対応するまでにかなり時間がかかるものもある(対応力を発揮する前に、確実に倒れてしまうだろう)。
関連記事:歩き方を即興で変えることのできる昆虫ロボットは本物の昆虫そっくりだ
Facebook AI(フェイスブックAI)、UC Berkeley(カリフォルニア大学バークレー校)、Carnegie Mellon University(カーネギーメロン大学)の研究チームは、この新しい動作モデルを「Rapid Motor Adaptation(迅速運動適応)」と呼んでいる。これは、人間や他の動物が、さまざまな状況に合わせて、すばやく、効果的に、無意識のうちに歩き方を変えられることに由来している。
「例えば、歩けるようになってから、初めて砂浜に行ったとします。足が沈み込み、それを引き上げるためには、より大きな力を加えなければなりません。違和感は覚えるでしょうが、数歩歩けば固い地面を歩くのと同じように自然に歩けるようになるでしょう。そこにはどんな秘密があるのでしょうか?」と、Facebook AIとカリフォルニア大学バークレー校に所属する上級研究員のJitendra Malik(ジテンドラ・マリク)氏は問いかける。
確かに、砂浜に行ったことがなかった人でも、人生の後半になってから初めて浜辺に行った人でさえ、すぐに自然に歩くことができる。柔らかい場所を歩くために、特別な「サンドモード」に切り替えているわけではない。動き方を変えることは自動的に行われ、外部環境を完全に理解する必要もない。
シミュレーション環境を視覚化したもの。もちろん、ロボットはこれらを視覚的に認識することはない(画像クレジット:Berkeley AI Research, Facebook AI Research and CMU)
「置かれた状態に違いが生じると、その影響によって身体自体に生じる違いを、身体が感知してそれに反応するのです」と、マリク氏は説明する。RMAシステムも同じように機能する。「歩く場所の環境が変わると、0.5秒以下の非常に短い時間で十分な測定を行い、その環境が何であるかを推定し、歩行の方針を修正します」。
システムはすべて、現実世界をバーチャルで再現したシミュレーションで訓練された。そこでは、ロボットの小さな頭脳(すべてはロボットに搭載されている限られた計算ユニット上でローカルに実行される)が、(仮想)関節や加速度計などの物理的なセンサーから送られてくるデータを、即座に認知して応答し、転倒を回避しながら最小限のエネルギーで最大限の前進を行う歩き方を学習した。
マリク氏はこのロボットが視覚入力を一切使用していないことを指摘し、RMAアプローチの完全な内部性を強調する。しかし、視覚を持たない人間や動物だって普通に歩けるのだから、ロボットにできないことがあるだろうか?歩いている砂や岩の正確な摩擦係数などの「外部性」を推定することは不可能なので、このロボットは自分自身に注意を向けるだけということになる。
「私たちは砂について学ぶのではなく、足が沈むことについて学ぶのです」と、共同研究者であるバークレー校のAshish Kumar(アシシュ・クマール)氏は述べている。
根本的にこのシステムは2つの部分から成り立っている。1つはロボットの歩行を実際に制御する常時稼働のメインアルゴリズム。そしてもう1つは、それと並行して作動し、ロボットの内部情報の変化を監視する対応アルゴリズムだ。顕著な変化が検出されると、それを分析して「足はこうなっているはずだが、こうなっているということは、状況はこうなっているということだ」と、メインモデルに調整方法を指示する。それ以降、ロボットは変化した状況下においても、どのように前進するかということだけを考え、実質的に即興で状況に合わせた歩行を行うようになる。
シミュレーションによるトレーニングを経て、このロボットは以下のようにニュースリリースにあるとおり、現実の世界でも見事に狙いを成功させた。
このロボットは砂、泥、ハイキングコース、背の高い草、土の山など、すべての実験で一度も失敗することなく歩行できました。ハイキングコースでは、70%の成功率で階段を降りることができました。セメントの山や小石の山では、訓練中に初めて出くわす不安定な地面や沈む地面、障害物となる植物、階段などがあったにもかかわらず、80%の成功率で乗り越えることができました。また、体重の100%に相当する12kgの荷物を積載して移動する際にも、高い成功率で身体の高さを維持することができました。
画像クレジット: Berkeley AI Research, Facebook AI Research and CMU
このような多くの状況における歩行の例は、こちらの動画や上の(ごく簡単な)GIFで見ることができる。
マリク氏は、NYU(ニューヨーク大学)のKaren Adolph(カレン・アドルフ)教授の研究を参考にした。同教授の研究では、人間が歩き方を覚えるプロセスが、いかに対応性が高く、自由な形態であるかを示している。どんな状況にも対応できるロボットを作るには、さまざまなモードを用意してそこから選ぶようにするのではなく、はじめから対応力を身につけなければならないというのが、チームの直感だった。
すべての物体や相互作用を網羅的にラベル付けして文書化しても、洗練されたコンピュータビジョンのシステムを構築することはできないのと同じように、砂利道、泥道、瓦礫、濡れた木の上などを歩くために、それぞれ専用のパラメータを10個、100個、さらには数千個も用意しても、多様で複雑な現実の世界にロボットを対応させることはできない。さらに言えば、ただ「前進せよ」という一般的な概念以外のことは何も指定しなくても済むようになるのが理想だ。
「脚の形状やロボットの形態については、あらかじめ一切プログラムしていません」と、クマール氏は述べている。
つまり、このシステムの基本部分は、四足歩行ロボットだけでなく、他の脚を持つロボットや、さらにはまったく別のAIやロボット工学の分野にも応用できる可能性があるということだ。
「ロボットの脚は手の指にも似ています。脚が環境と相互作用するように、指は物体と相互作用します」と、共同執筆者であるCarnegie Mellon University(カーネギーメロン大学)のDeepak Pathak(ディーパック・パターク)氏は指摘する。「基本的な考え方は、どんなロボットにも適用できます」。
さらにマリク氏は、基本アルゴリズムと対応アルゴリズムの組み合わせが、他のインテリジェントなシステムにも応用できることを示唆している。スマートホームや自治体のシステムは、既存のポリシーに依存する傾向があるが、しかし、状況に応じてその場で対応できるようになったらどうだろう?
今のところ、チームは初期の研究成果を「Robotics:Science and Systems(ロボット工学:科学とシステム)」会議で論文として発表しているだけであり、まだ多くのフォローアップ研究が必要であることを認めている。例えば、即興的な動作を「中期的な」記憶として内部にライブラリー化したり、視覚を利用して新しいスタイルの運動を開始する必要性を予測したりすることなどが考えられる。とはいえ、RMAのアプローチは、ロボット工学の永遠の課題に対する将来性の高い新たなアプローチとして期待が持てそうだ。
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画像クレジット:Berkeley AI Research, Facebook AI Research and CMU
【原文】
Robots have a hard time improvising, and encountering an unusual surface or obstacle usually means an abrupt stop or hard fall. But researchers have created a new model for robotic locomotion that adapts in real time to any terrain it encounters, changing its gait on the fly to keep trucking when it hits sand, rocks, stairs and other sudden changes.
Although robotic movement can be versatile and exact, and robots can “learn” to climb steps, cross broken terrain and so on, these behaviors are more like individual trained skills that the robot switches between. Although robots like Spot famously can spring back from being pushed or kicked, the system is really just working to correct a physical anomaly while pursuing an unchanged policy of walking. There are some adaptive movement models, but some are very specific (for instance this one based on real insect movements) and others take long enough to work that the robot will certainly have fallen by the time they take effect.
The team, from Facebook AI, UC Berkeley and Carnegie Mellon University, call it Rapid Motor Adaptation. It came from the fact that humans and other animals are able to quickly, effectively and unconsciously change the way they walk to fit different circumstances.
“Say you learn to walk and for the first time you go to the beach. Your foot sinks in, and to pull it out you have to apply more force. It feels weird, but in a few steps you’ll be walking naturally just as you do on hard ground. What’s the secret there?” asked senior researcher Jitendra Malik, who is affiliated with Facebook AI and UC Berkeley.
Certainly if you’ve never encountered a beach before, but even later in life when you have, you aren’t entering some special “sand mode” that lets you walk on soft surfaces. The way you change your movement happens automatically and without any real understanding of the external environment.
Visualization of the simulation environment. Of course the robot would not perceive any of this visually. Image Credits: Berkeley AI Research, Facebook AI Research and CMU
“What’s happening is your body responds to the differing physical conditions by sensing the differing consequences of those conditions on the body itself,” Malik explained — and the RMA system works in similar fashion. “When we walk in new conditions, in a very short time, half a second or less, we have made enough measurements that we are estimating what these conditions are, and we modify the walking policy.”
The system was trained entirely in simulation, in a virtual version of the real world where the robot’s small brain (everything runs locally on the on-board limited compute unit) learned to maximize forward motion with minimum energy and avoid falling by immediately observing and responding to data coming in from its (virtual) joints, accelerometers and other physical sensors.
To punctuate the total internality of the RMA approach, Malik notes that the robot uses no visual input whatsoever. But people and animals with no vision can walk just fine, so why shouldn’t a robot? But since it’s impossible to estimate the “externalities” such as the exact friction coefficient of the sand or rocks it’s walking on, it simply keeps a close eye on itself.
“We do not learn about sand, we learn about feet sinking,” said co-author Ashish Kumar, also from Berkeley.
Ultimately the system ends up having two parts: a main, always-running algorithm actually controlling the robot’s gait, and an adaptive algorithm running in parallel that monitors changes to the robot’s internal readings. When significant changes are detected, it analyzes them — the legs should be doing this, but they’re doing this, which means the situation is like this — and tells the main model how to adjust itself. From then on the robot only thinks in terms of how to move forward under these new conditions, effectively improvising a specialized gait.
Image Credits: Berkeley AI Research, Facebook AI Research and CMU
After training in simulation, it succeeded handsomely in the real world, as the news release describes it:
The robot was able to walk on sand, mud, hiking trails, tall grass and a dirt pile without a single failure in all our trials. The robot successfully walked down stairs along a hiking trail in 70% of the trials. It successfully navigated a cement pile and a pile of pebbles in 80% of the trials despite never seeing the unstable or sinking ground, obstructive vegetation or stairs during training. It also maintained its height with a high success rate when moving with a 12 kg payload that amounted to 100% of its body weight.
You can see examples of many of these situations in videos here or (very briefly) in the gif above.
Malik gave a nod to the research of NYU professor Karen Adolph, whose work has shown how adaptable and free-form the human process of learning how to walk is. The team’s instinct was that if you want a robot that can handle any situation, it has to learn adaptation from scratch, not have a variety of modes to choose from.
Just as you can’t build a smarter computer-vision system by exhaustively labeling and documenting every object and interaction (there will always be more), you can’t prepare a robot for a diverse and complex physical world with 10, 100, even thousands of special parameters for walking on gravel, mud, rubble, wet wood, etc. For that matter you may not even want to specify anything at all beyond the general idea of forward motion.
“We don’t pre-program the idea that it has for legs, or anything about the morphology of the robot,” said Kumar.
This means the basis of the system — not the fully trained one, which ultimately did mold itself to quadrupedal gaits — can potentially be applied not just to other legged robots, but entirely different domains of AI and robotics.
“The legs of a robot are similar to the fingers of a hand; the way that legs interact with environments, fingers interact with objects,” noted co-author Deepak Pathak, of Carnegie Mellon University. “The basic idea can be applied to any robot.”
Even further, Malik suggested, the pairing of basic and adaptive algorithms could work for other intelligent systems. Smart homes and municipal systems tend to rely on preexisting policies, but what if they adapted on the fly instead?
For now the team is simply presenting their initial findings in a paper at the Robotics: Science and Systems conference and acknowledge that there is a great deal of follow-up research to do. For instance building an internal library of the improvised gaits as a sort of “medium-term” memory, or using vision to predict the necessity of initiating a new style of locomotion. But the RMA approach seems to be a promising new approach for an enduring challenge in robotics.
(文:Devin Coldewey、翻訳:Hirokazu Kusakabe)
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I think the idea that they’re potentially harming our health is too much for some people.” Since cellphones first came onto the market in 1983, they have gone from clunky devices with bad reception to today’s sleek, multifunction smartphones. And although cellphones are now used by nearly all American adults, considerable research suggests that long-term use poses health risks from the radiation they emit, said Moskowitz. “Cellphones, cell towers and other wireless devices are regulated by most governments,” said Moskowitz. “Our government, however, stopped funding research on the health effects of radiofrequency radiation in the 1990s.” Since then, he said, research has shown significant adverse biologic and health effects — including brain cancer — associated with the use of cellphones and other wireless devices. And now, he said, with the fifth generation of cellular technology, known as 5G, there is an even bigger reason for concern. Berkeley News spoke with Dr Moskowitz about the health risks of cellphone radiation, why the topic is so controversial and what we can expect with the rollout of 5G. * Berkeley News: I first heard you speak about the health risks of cellphone radiation at Berkeley in 2019, but you’ve been doing this research since 2009. What led you to pursue this research? Joel Moskowitz: I got into this field by accident, actually. During the past 40 years, the bulk of my research has been focused on tobacco-related disease prevention. I first became interested in cellphone radiation in 2008, when Dr. Seung-Kwon Myung, a physician scientist with the National Cancer Center of South Korea, came to spend a year at the Center for Family and Community Health. He was involved in our smoking cessation projects, and we worked with him and his colleagues on two reviews of the literature, one of which addressed the tumor risk from cellphone use. At that time, I was skeptical that cellphone radiation could be harmful. However, since I was dubious that cellphone radiation could cause cancer, I immersed myself in the literature regarding the biological effects of low-intensity microwave radiation, emitted by cellphones and other wireless devices.After reading many animal toxicology studies that found that this radiation could increase oxidative stress — free radicals, stress proteins and DNA damage — I became increasingly convinced that what we were observing in our review of human studies was indeed a real risk. BN: While Myung and his colleagues were visiting the Center for Family and Community Health, you reviewed case-control studies examining the association between mobile phone use and tumor risk. What did you find? JM: Our 2009 review, published in the Journal of Clinical Oncology, found that heavy cellphone use was associated with increased brain cancer incidence, especially in studies that used higher quality methods and studies that had no telecommunications industry funding. Last year, we updated our review, published in the International Journal of Environmental Research and Public Health, based on a meta-analysis of 46 case-control studies — twice as many studies as we used for our 2009 review — and obtained similar findings. Our main takeaway from the current review is that approximately 1,000 hours of lifetime cellphone use, or about 17 minutes per day over a 10-year period, is associated with a statistically significant 60% increase in brain cancer. BN: One thing I think we should address upfront is how controversial this research is. Some scientists have said that these findings are without basis and that there isn’t enough evidence that cellphone radiation is harmful to our health. How do you respond to that? JM: Well, first of all, few scientists in this country can speak knowledgeably about the health effects of wireless technology. So, I’m not surprised that people are skeptical, but that doesn’t mean the findings aren’t valid. A big reason there isn’t more research about the health risks of radiofrequency radiation exposure is because the U.S. government stopped funding this research in the 1990s, with the exception of a $30 million rodent study published in 2018 by the National Institute of Environmental Health Sciences’ National Toxicology Program, which found “clear evidence” of carcinogenicity from cellphone radiation.In 1996, the Federal Communications Commission, or FCC, adopted exposure guidelines that limited the intensity of exposure to radiofrequency radiation. These guidelines were designed to prevent significant heating of tissue from short-term exposure to radiofrequency radiation, not to protect us from the effects of long-term exposure to low levels of modulated, or pulsed, radiofrequency radiation, which is produced by cellphones, cordless phones and other wireless devices, including Wi-Fi. Yet, the preponderance of research published since 1990 finds adverse biologic and health effects from long-term exposure to radiofrequency radiation, including DNA damage. More than 250 scientists, who have published over 2,000 papers and letters in professional journals on the biologic and health effects of non-ionizing electromagnetic fields produced by wireless devices, including cellphones, have signed the International EMF Scientist Appeal, which calls for health warnings and stronger exposure limits. So, there are many scientists who agree that this radiation is harmful to our health. BN: Why did the government stop funding this kind of research? JM: The telecommunications industry has almost complete control of the FCC, according to Captured Agency, a monograph written by journalist Norm Alster during his 2014-15 fellowship at Harvard University’s Center for Ethics. There’s a revolving door between the membership of the FCC and high-level people within the telecom industry that’s been going on for a couple of decades now. The industry spends about $100 million a year lobbying Congress. The CTIA, which is the major telecom lobbying group, spends $12.5 million per year on 70 lobbyists. According to one of their spokespersons, lobbyists meet roughly 500 times a year with the FCC to lobby on various issues. The industry as a whole spends $132 million a year on lobbying and provides $18 million in political contributions to members of Congress and others at the federal level. BN: It reminds me of when the U.S. Surgeon General released a landmark report in 1964 that linked cigarettes with dangerous health effects, including cancer and heart disease. Even though the 10-person committee consulted more than 7,000 articles already available in biomedical literature, the report’s findings were very controversial when they came out. JM: Yes, there are strong parallels between what the telecom industry has done and what the tobacco industry has done, in terms of marketing and controlling messaging to the public. In the 1940s, tobacco companies hired doctors and dentists to endorse their products to reduce public health concerns about smoking risks. The CTIA currently uses a nuclear physicist from academia to assure policymakers that microwave radiation is safe. The telecom industry not only uses the tobacco industry playbook, it is more economically and politically powerful than Big Tobacco ever was. This year, the telecom industry will spend over $18 billion advertising cellular technology worldwide. BN: You mentioned that cellphones and other wireless devices use modulated, or pulsed, radiofrequency radiation. Can you explain how cellphones and other wireless devices work, and how the radiation they emit is different from radiation from other household appliances, like a microwave? JM: Basically, when you make a call, you’ve got a radio and a transmitter. It transmits a signal to the nearest cell tower. Each cell tower has a geographic cell, so to speak, in which it can communicate with cellphones within that geographic region or cell. Then, that cell tower communicates with a switching station, which then searches for whom you’re trying to call, and it connects through a copper cable or fiber optics or, in many cases, a wireless connection through microwave radiation with the wireless access point. Then, that access point either communicates directly through copper wires through a landline or, if you’re calling another cellphone, it will send a signal to a cell tower within the cell of the receiver and so forth.The difference is the kind of microwave radiation each device emits. With regard to cellphones and Wi-Fi and Bluetooth, there is an information-gathering component. The waves are modulated and pulsed in a very different manner than your microwave oven. BN: What, specifically, are some of the health effects associated with long-term exposure to low-level modulated radiofrequency radiation emitted from wireless devices? JM: Many biologists and electromagnetic field scientists believe the modulation of wireless devices makes the energy more biologically active, which interferes with our cellular mechanisms, opening up calcium channels, for example, and allowing calcium to flow into the cell and into the mitochondria within the cell, interfering with our natural cellular processes and leading to the creation of stress proteins and free radicals and, possibly, DNA damage. And, in other cases, it may lead to cell death. In 2001, based upon the biologic and human epidemiologic research, low-frequency fields were classified as “possibly carcinogenic” by the International Agency for Research on Cancer (IARC) of the World Health Organization. In 2011, the IARC classified radiofrequency radiation as “possibly carcinogenic to humans,” based upon studies of cellphone radiation and brain tumor risk in humans. Currently, we have considerably more evidence that would warrant a stronger classification. Most recently, on March 1, 2021, a report was released by the former director of the National Center for Environmental Health at the Centers for Disease Control and Prevention, which concluded that there is a “high probability” that radiofrequency radiation emitted by cellphones causes gliomas and acoustic neuromas, two types of brain tumors. BN: Let’s talk about the fifth generation of cellphone technology, known as 5G, which is already available in limited areas across the U.S. What does this mean for cellphone users and what changes will come with it? JM: For the first time, in addition to microwaves, this technology will employ millimeter waves, which are much higher frequency than the microwaves used by 3G and 4G. Millimeter waves can’t travel very far, and they’re blocked by fog or rain, trees and building materials, so the industry estimates that it’ll need 800,000 new cell antenna sites.Each of these sites may have cell antennas from various cellphone providers, and each of these antennas may have microarrays consisting of dozens or even perhaps hundreds of little antennas. In the next few years in the U.S., we will see deployed roughly 2.5 times more antenna sites than in current use unless wireless safety advocates and their representatives in Congress or the judicial system put a halt to this. BN: How are millimeter waves different from microwaves, in terms of how they affect our bodies and the environment? JM: Millimeter wave radiation is largely absorbed in the skin, the sweat glands, the peripheral nerves, the eyes and the testes, based upon the body of research that’s been done on millimeter waves. In addition, this radiation may cause hypersensitivity and biochemical alterations in the immune and circulatory systems — the heart, the liver, kidneys and brain.Millimeter waves can also harm insects and promote the growth of drug-resistant pathogens, so it’s likely to have some widespread environmental effects for the microenvironments around these cell antenna sites. BN: What are some simple things that each of us can do to reduce the risk of harm from radiation from cellphones and other wireless devices? JM: First, minimize your use of cellphones or cordless phones — use a landline whenever possible. If you do use a cellphone, turn off the Wi-Fi and Bluetooth if you’re not using them. However, when near a Wi-Fi router, you would be better off using your cellphone on Wi-Fi and turning off the cellular because this will likely result in less radiation exposure than using the cellular network. Second, distance is your friend. Keeping your cellphone 10 inches away from your body, as compared to one-tenth of an inch, results in a 10,000-fold reduction in exposure. So, keep your phone away from your head and body. Store your phone in a purse or backpack. If you have to put it in your pocket, put it on airplane mode. Text, use wired headphones or speakerphone for calls. Don’t sleep with it next to your head — turn it off or put it in another room. Third, use your phone only when the signal is strong. Cellphones are programmed to increase radiation when the signal is poor, that is when one or two bars are displayed on your phone. For example, don’t use your phone in an elevator or in a car, as metal structures interfere with the signal. Also, I encourage people to learn more about the 150-plus local groups affiliated with Americans for Responsible Technology, which are working to educate policymakers, urging them to adopt cell tower regulations and exposure limits that fully protect us and the environment from the harm caused by wireless radiation. For safety tips on how to reduce exposure to wireless radiation from the California Department of Public Health and other organizations, visit Moskowitz’s website, saferemr.com, Physicians for Safe Technology and the Environmental Health Trust. * Note to readers: Please click the share buttons above or below. Follow us on Instagram, @crg_globalresearch. Forward this article to your email lists. Crosspost on your blog site, internet forums. etc. Related Articles
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