Contoro picks up $12M to scale container unloading robots

States Logistics in California was an early user of Contoro’s truck-unloading robot.

Unloading trailers and containers is a labor-intensive task that has been difficult to automate, but a number of companies have made progress. Contoro Robotics today said it has raised $12 million in Series A funding to scale its artificial intelligence-powered robots.

“Unloading trailers is one of the most physically demanding jobs in the warehouse, yet it remains largely manual,” stated Dr. Youngmok “Mok” Yun, founder and CEO of Contoro Robotics. “We’re bringing AI-powered automation that enhances reliability, safety, and efficiency—allowing warehouse teams to shift from hazardous, repetitive tasks to more strategic and value-added roles.”

Yun studied human-machine interaction (HMI) at the University of Texas at Austin. After getting his Ph.D., Yun co-founded Harmonic Bionics Inc., which commercialized a system to help patients relearn tasks after a stroke.

“Our original research was funded by NASA and the NSF. Contoro is a spinoff from Harmonic Bionics,” he told The Robot Report. “At Harmonic Bionics, we used automation to help people learn. At Contoro, we’re using the human-robot interface in reverse. Contoro uses the human intelligence to help robots learn.”

Founded in 2022, Contoro Robotics uses a human-in-the-loop (HITL) model to close the gap between AI robotics performance and industrial needs, Yun explained. The Austin, Texas-based company said this approach can achieve over 99% success in real-world applications, increasing the commercial viability of robotic unloading of floor-loaded shipping containers.

“Unloading containers has many problems — parcels, pallets, and even furniture — but we’re mainly focused on unloading boxes from ocean containers,” said Yun. “The U.S. imports about 26 million each year, and they’re currently unloaded by hand.”

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Contoro uses custom AI and grippers

“For years, automation has struggled to unload multi-SKU, floor-loaded trailers,” noted Contoro Robotics. “It is an unpredictable process filled with different-sized boxes, shifting loads, and ever-changing packaging.”

The company said it has developed customer-specific AI models, innovative grasping techniques, and HITL oversight. Contoro initially trained its robots with teleoperation, but its AI can now learn on its own, with human intervention only for exception handling. One person can oversee more than 10 robots, Yun said.

“Our robot can unload 97% to 98% in the first week, because box designs change, challenging the AI,” he said. “With a human in the loop, it can then handle 99.5% after a week. We have multiple layers to make human intervention easy as needed, with AI, remote support, then customer intervention.”

Yun noted that HITL is one of the key technologies leading to Contoro’s success in unloading. This human-in-the-loop approach has also been proven by another Texas-based warehouse robotics company, Plus One Robotics Inc.

Contoro used teleoperation to initially train its unloading robots. Source: Contoro

In addition, Contoro created Duo-Grasp, a proprietary two-point gripping system, to securely handle a wider range of box sizes and weights than competing end effectors.

“Our gripper is articulated and can grasp from two sides with suction cups,” said Yun. “It can lift up to 80 lb. [36.2 kg] boxes with front and side grasping, which are required by companies that unload large and heavy boxes, such as in the furniture and home appliance industries.”

Contoro claimed that its technologies enable highly reliable unloading, even in unpredictable freight logistics environments that are typically challenging for robots. Its system can pick more than 300 to 350 cases per hour.

“We typically exceed that at customer sites, and we can do multi-picking of smaller and lighter boxes,” said Yun. “While a human can typically pick 500 to 700 items per hour, we can reliably unload heavy boxes constantly without ergonomic strain because of our human in the loop. Companies don’t want to drop appliances or food cases.”

Series A draws additional investors

Contoro has combined its AI with a custom gripper, a mobile base, and a KUKA arm. Source: Contoro Robotics

As the warehousing and logistics industry faces ongoing labor shortages and rising costs, investors are looking for scalable, commercially viable approaches to robotics.

New investors Doosan, Coupang, the Amazon Industrial Innovation Fund, and IMM participated in Contoro Robotics’ Series A round. They joined existing backers SV Investment, KB Investment, Kakao Ventures, and Future Play, bringing Contoro’s total funding to $22 million.

“Trailer unloading is one of the most labor-intensive and manual processes in the warehouse,” said Franziska Bossart, head of the Amazon Industrial Innovation Fund. “We believe Contoro is making meaningful progress to tackle this challenge with its unique end effector and teleop-augmented AI.”

Other companies working on loading and unloading robots include Anyware Robotics (which also raised $12 million last week), Boston Dynamics, Dexterity, Lab0, Pickle Robot, and Slip Robotics. They and Contoro showed their different approaches at ProMat in Chicago last week.

Robotic unloading to spread

Contoro Robotics said that early deployments have already doubled unloading speed, reduced dependency on manual labor, and saved hundreds of labor hours per month for customers facing rising costs and operational bottlenecks. Its initial robots are in Texas and Southern California, with more coming to New Jersey and other locations soon.

The company added that its pay-per-container pricing model, a variation on robotics as a service (RaaS), removes the barrier of upfront capital costs and makes automation an attractive alternative to traditional lumping services.

“Our business model is unique, and we want to make adoption easy,” Yun said. “For example, one customer is a calendar company that has big seasonality, so we can take the robots back outside of Q3 and Q4.”

Contoro plans to manufacture more robots, with final assembly in Austin. It also plans to expand into new logistics markets and launch its next-generation AI-driven palletizing system.

The company asserted that its robots are already helping warehouses, distribution centers, and e-commerce fulfillment hubs cut costs and increase throughput “without the headaches of traditional automation deployments.”

“Our customers are loving our robots, and we are going to rapidly expand our deployments across the U.S. market,” said Yun. “I believe that the future of this market is great, and we’re attacking a small subset of the entire problem.”

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