Eka Robotics 是一家位于马萨诸塞州剑桥的初创公司，致力于开发既能通过触觉又能通过视觉操作物体的机器人，该公司已完成 1.5 亿美元的 A 轮融资。Eka 周二在其博客上宣布，Andreessen Horowitz (a16z) 和 F-Prime 领投了本轮融资。据 TechCrunch 的 Tim Fernholz 报道，本轮融资后该公司估值为 14.5 亿美元。
Eka Robotics, a Cambridge, Massachusetts startup building robots that handle objects by touch as well as sight, has raised a $150M Series A. Andreessen Horowitz (a16z) and F-Prime led the round, Eka announced on its blog on Tuesday. The round values the company at $1.45B post-money, Tim Fernholz reported for TechCrunch.
F-Prime 是一家与 FMR（富达投资的母公司）有关联的风险投资基金。曾领投 Eka 种子轮的 Obvious Ventures 和 E14 Fund 继续跟投。MFV Partners、Bison Ventures、Glasswing Ventures、Samsung Next 以及几家未透露名称的大公司也参与了投资。Eka 表示，这笔资金将帮助其在更多任务上训练模型，并加快客户部署进度。
F-Prime is a venture fund linked to FMR, the parent company of Fidelity Investments. Obvious Ventures and E14 Fund, which led Eka’s seed round, invested again. MFV Partners, Bison Ventures, Glasswing Ventures, Samsung Next and several unnamed large companies also took part. Eka says the money will help it train its model on more tasks and speed up customer deployments.
触觉，而非仅靠视觉 许多机器人 AI 模型将机器人看到的内容与接收到的指令关联到其采取的行动上。Eka 的模型则加入了力觉。它将视觉与机器人手部力传感器的反馈相结合，使机器人能感觉到抓握滑移并进行修正。
Touch, not only sight Many robot AI models connect what a robot sees and the instructions it gets to the actions it takes. Eka’s model adds force. It combines vision with feedback from force sensors in the robot’s hand, so the robot can feel a grip slipping and correct it.
“视觉并非解决‘最后一毫米’问题的主要方式。视觉只能大致告诉你物体在哪里、姿态如何，但实际的抓取、实际的搜寻是通过力来完成的，”联合创始人 Pulkit Agrawal 对 TechCrunch 表示。
“Vision is not the primary way in which you close this last millimeter problem. Vision tells you roughly where the object is, what the pose is, but the actual grabbing, the actual searching is happening through forces,” co-founder Pulkit Agrawal told TechCrunch.
据 TechCrunch 报道，Eka 为此专门设计了自己的手，配备的力传感器比标准夹爪更多。Agrawal 称，该硬件成本低于 1000 美元。其额定寿命为 500 万次工作循环，目标是达到 2000 万次，达到标准工业机械臂的水平。
Eka designed its own hand for this, with more force sensors than a standard gripper, TechCrunch reported. Agrawal said the hardware costs less than $1,000. It is rated for 5 million duty cycles, and the goal is 20 million, the level of standard industrial arms.
其他公司也在研究机器人触觉。苏黎世的 Enact 本周融资 3000 万美元，旨在赋予机器人触觉。在中国，机器人手制造商 Linkerbot 于 5 月寻求 60 亿美元估值。
Others are working on robot touch too. Zurich’s Enact raised $30M this week to give robots a sense of touch. In China, robot-hand maker Linkerbot was seeking a $6bn valuation in May.
在仿真中练习 机器人行业的大部分企业通过记录人类执行任务的过程来训练机器。Eka 则采用强化学习，在物理仿真器中通过试错进行训练，随后将技能迁移到真实硬件上。该公司表示，能在几分钟内生成数千小时的机器人经验。
Practice in simulation Much of the robotics industry teaches machines with recordings of people doing the task. Eka trains by trial and error in a physics simulator instead, using reinforcement learning, then moves the skills onto real hardware. It says it can generate thousands of hours of robot experience in minutes.
创始人是在加州大学伯克利分校攻读研究生时相识的。Agrawal 领导麻省理工学院的 Improbable AI 实验室。Tuomas Haarnoja 曾在 Google DeepMind 工作，并共同创造了广泛使用的强化学习算法 Soft Actor-Critic。
The founders met as graduate students at the University of California, Berkeley. Agrawal leads the Improbable AI Lab at MIT. Tuomas Haarnoja worked at Google DeepMind and co-created Soft Actor-Critic, a widely used reinforcement learning algorithm.
其他初创企业则收集人类数据。Maxinsights 本周融资 3000 万美元，旨在将家务劳动转化为机器人训练数据。
Other startups collect human data instead. Maxinsights raised $30M this week to turn household chores into robot training data.
每小时拣选 1500 件 Eka 称，其机器人拣选未经训练过的物体，速度可达每小时 1500 件，约为人类每小时 600 件左右速度的两倍半。同一台机器人既能拧灯泡，也能插电线。据 TechCrunch 报道，它能处理重达 1 公斤的物体，成功率超过 95%。TNW 未核实这些数据。
1,500 picks an hour Eka says its robots pick objects they were not trained on at 1,500 an hour, about two and a half times the human rate of around 600. The same robot can screw in a light bulb and insert wires. According to TechCrunch, it handles objects of up to 1 kg and succeeds more than 95% of the time. TNW has not verified those figures.
“Eka 的视觉-力-动作模型是我见过的第一个真正解决了操作问题、具备部署所需的通用性和吞吐量的方法，”a16z 的 Raghu Raghuram 在 Eka 的声明中表示。
“Eka’s Vision-Force-Action model is the first approach I’ve seen that truly solves manipulation with the generality and throughput needed for deployments,” said Raghu Raghuram of a16z in Eka’s announcement.
伊利诺伊大学厄巴纳-香槟分校教授 Kris Hauser 告诉 TechCrunch，这款机器人具有“惊艳因素”，无需重新训练即可适应多种物体。
Kris Hauser, a professor at the University of Illinois Urbana-Champaign, told TechCrunch the robot had a “wow factor” and adapted to many objects without retraining.
工厂测试 据 TechCrunch 报道，Eka 正在与工业客户开展拣选放置和线缆处理方面的试点。该公司未透露客户名称。Hauser 表示，真正的考验在于生产线上。
The factory test Eka is running pilots with industrial customers in pick-and-place and wire handling, TechCrunch reported. It has not named them. Hauser said the real test comes on the production line.
“一个巨大的挑战将是，当他们与系统集成商在真实的装配线上合作时，机器人需要在不出故障的情况下运行整整一年，”Hauser 告诉 TechCrunch。
“What’s going to be a big challenge is when they work with integrators on real assembly lines, and it needs to run without breaking for an entire year,” Hauser told TechCrunch.