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机器人手公司Proception与特斯拉和解商业机密诉讼并宣布1100万美元融资

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22:0006/29 22:00社区阅读原文 ↗导出 MD ↓

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51

精选理由

话题涉及特斯拉商业机密案件的和解以及千万级融资,兼具法律与商业热点,对机器人行业有重要示范意义。

AI 点评

「这一和解与融资事件表明,机器人手技术在商业化和法律挑战中正走向成熟,可能加速人形机器人手部操作能力的突破。」

速览

机器人初创公司Proception与特斯拉就一起商业机密诉讼达成和解,并同步宣布完成1100万美元融资。该公司采用独特方法收集训练数据,致力于解决机器人领域最棘手的问题之一——灵巧手操作。这标志着人形机器人硬件与数据收集模式的重要突破。

  • Proception与特斯拉就商业机密诉讼达成和解,具体条款未披露。
  • 公司同步完成1100万美元融资,用于扩大机器人手的生产与数据收集。
  • Proception采用创新的训练数据收集方法,模拟真实环境中的手部操作。
  • 该公司目标是解决机器人领域最具挑战性的灵巧手操作问题。

正文

Jay Li doesn’t recommend getting sued by Tesla if you’re trying to get a startup off the ground. But he does think his company, Proception, might be better off for having endured the experience.

“I think it’s kind of like a resilience test, or pressure test,” he told TechCrunch in an exclusive interview. “People say that what doesn’t kill you makes you stronger, right?”

Li, who was a technical lead on Tesla’s Optimus humanoid robot program, was accused by his former employer last year of absconding with trade secrets to start Proception. But after months of trading legal blows, he finally reached a settlement with Tesla, which dismissed the lawsuit earlier this month. (Tesla did not respond to a request for comment.)

Now Li is free to tackle what he thinks is an even harder problem: making robot hands work like a human’s.

To help do that, Proception announced Monday that it has raised an $11 million seed round led by First Round Capital, with contributions from Y Combinator and early-stage fund BoxGroup.

Proception also announced Monday that it is shipping the first batch of its “high-dexterity robotic hand” to “researchers and robotics companies,” while opening up to wider orders. The goal, Li said, is to become the top hand supplier to other companies that don’t want to spend the time or resources developing what’s known in the industry as “dexterous manipulation.”

While there’s been an avalanche of money and attention rushing into the world of robotics, Li believes not enough of that has gone to making robotic hands truly mimic a human’s hands.

One of the loudest voices talking about this challenge has actually been his old boss, Tesla CEO Elon Musk, who has said robot hands are one of the biggest engineering problems yet to be solved.

While Musk has maintained that Optimus robots could start working in factories in a matter of years, the consensus view is that making robotic hands equivalent to a human’s is still many years away. Kevin Lynch, the director of Northwestern University’s Center for Robotics and Biosystems, told the Wall Street Journal last year that his team believes it will be a decade until they are “functional and useful and able to do some of the things that humans do.”

Li thinks Proception can do it much faster, in large part because of how they’re collecting data.

Most companies training humanoid robots right now are using teleoperators to train their systems. A human wearing a virtual-reality headset is able to see what a robot sees and manipulate what’s in front of that robot, then the robot can learn from the commands given by the human.

A big drawback to this approach, according to Li, is that the teleoperator is not receiving feedback from the objects the robot is touching. This approach is also limited to the number of robots a company has available at any given moment, Li said.

Proception’s solution is a glove laden with sensors. With human testers wearing the gloves (and a headset), Proception and its customers can capture “human hand interaction data without requiring a robot in the loop,” according to Proception’s press release.

This same glove also goes on the hand Proception is developing, acting as its sensor-packed “skin.” The hand has 22 degrees of freedom and multiple joints per finger to enable a “wide range of dexterous motions,” according to Proception.

Li said this approach will also let Proception and its customers gather finer, more task-specific data that can allow its robotic hands to more accurately resemble a human’s. He also thinks it is better suited to scale up.

“You need both hardware and data, and those need to come hand-in-hand to get [dextrous manipulation] to work. A lot of companies solely focus on hardware, or like hardware plus non-scalable data [collection],” he said. “We’re working on this highly dexterous hardware plus highly scalable data. We believe that’s a key combination to solve this problem.”

First Round partner Bill Trenchard, who led the investment in Proception, said this was a big reason why he backed Li.

“We think they will have the best hand in the market, maybe the most sophisticated hand today, and the underlying data and models to support that,” he told TechCrunch. “Dexterous manipulation is a very, very, very important part of the whole humanoid story going forward, and as many people have said, it’s sort of the last mile of getting these robots to be truly performant.”

Trenchard also praised Li’s ability to keep a cool head while being sued by his former employer.

“He was very upfront with us when this came out, and I think the team did an amazing job of keeping their heads down,” Trenchard said. “Jay’s a very strong leader.”

Li is also confident. After facing down Tesla’s “hardcore litigation department,” he told TechCrunch that he wouldn’t be surprised if the company comes calling for help as Proception grows.

“I think it will happen,” he said.

Topics

AI, Exclusive, proception, Robotics, robotics

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Sean O'Kane Sean O'Kane

Sr. Reporter, Transportation

Sean O’Kane is a reporter who has spent a decade covering the rapidly-evolving business and technology of the transportation industry, including Tesla and the many startups chasing Elon Musk. Most recently, he was a reporter at Bloomberg News where he helped break stories about some of the most notorious EV SPAC flops. He previously worked at The Verge, where he also covered consumer technology, hosted many short- and long-form videos, performed product and editorial photography, and once nearly passed out in a Red Bull Air Race plane.

You can contact or verify outreach from Sean by emailing sean.okane@techcrunch.com or via encrypted message at okane.01 on Signal.

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