Chef Robotics has designed its robotic system to deal with high-mix meals preparation. | Supply: Chef Robotics
Bodily AI has made outstanding strides, however more often than not, we use inflexible objects to coach basis fashions. Meals represents probably the most complicated manipulation challenges in robotics, famous Chef Robotics. Each ingredient is deformable, inconsistent in weight and texture, delicate to temperature, and should be dealt with with calibrated pressure throughout hundreds of variations.
Chef Robotics stated it has constructed the biggest real-world dataset of deformable materials manipulation. The corporate has accomplished over 118 million servings in manufacturing throughout over a dozen meals manufacturing services in North America and Europe. This information serves as the premise for its Meals Basis Mannequin (FFM), which allows robots to generalize to new substances with minimal retraining.
At RoboBusiness 2026 on Oct. 20 and 21 in Santa Clara, Calif., Rajat Bhageria, the founder and CEO of Chef Robotics, will give the discuss, “Why Meals is Bodily AI’s Hardest Drawback and Most Promising Catalyst.”
Chef CEO to discover challenges, alternatives for meals robotics
This session will discover what makes meals such a demanding benchmark for bodily AI. This contains:
- The sensor-fusion challenges of greedy comfortable and unpredictable objects
- The force-control precision required to deal with fragile versus dense supplies
- Why real-world variation at scale is irreplaceable for coaching sturdy insurance policies
Extra importantly, Bhageria will present why fixing meals unlocks progress far past this business. The strategies developed at Chef Robotics — comparable to adaptive greedy, tactile suggestions integration, and high-variance coaching distributions — could switch to medical gadgets, versatile packaging, agriculture, and different domains involving deformable supplies.
Attendees will go away with a concrete framework for fascinated with deformable materials manipulation as the following frontier in bodily AI, and proof that real-world information at scale is what separates lab demos from deployable programs.
San Francisco-based Chef Robotics is a bodily AI firm that automates meals manufacturing. Beforehand, Bhageria was a founder and managing accomplice at Prototype Capital, a pre-seed enterprise capital fund investing in founders who apply new know-how to previous industries.
Earlier than Prototype Capital, Bhageria based ThirdEye, an organization that developed assistive know-how for the visually impaired. ThirdEye was in the end acquired. Bhageria holds a grasp’s diploma in robotics and machine studying and a bachelor’s diploma in economics from the College of Pennsylvania.
Register now for RoboBusiness 2026
RoboBusiness 2026 is the main occasion for business robotics builders. Attendees will acquire the newest insights from specialists in robotics and AI on cutting-edge analysis, business developments, and progressive functions in sectors comparable to manufacturing, healthcare, agriculture, logistics, and extra.
The present additionally options quite a lot of networking opportunities to provide attendees the prospect to attach with different specialists within the business. It will embrace the Combine and Mingle reception on the primary day of the present.
Buy your full conference pass and acquire full entry to all keynotes, technical periods, networking receptions, and particular occasions. Reductions are additionally accessible for academia, associations, and company teams. Please electronic mail occasions[at]arrowfly.com for extra particulars about our low cost applications.
For details about sponsorship and exhibition alternatives, download the prospectus. Questions concerning sponsorship alternatives must be directed to Colleen Sepich at csepich[AT]arrowfly.com.
Register now and save in your cross to RoboBusiness 2026The put up Be taught why meals is bodily AI’s hardest drawback at RoboBusiness appeared first on The Robotic Report.
