Jeff Cardenas of Apptronik discusses humanoid robot safety, deployment scale, and product design with the Automated Podcast host at the Humanoid Robot Forum.
Cardenas expects wheeled humanoids to find early use in places such as health care, where buildings are already designed for wheeled mobility. Legs can help in compact spaces and tasks like reaching the back of a pallet, while a wheeled base can simplify some deployments. Apptronik’s Apollo can use legs, a stationary mount, or wheels, with a modular upper body.
Cardenas describes three levels: barrier guarded operation, cooperative operation that pauses or moves to a safe position near people, and collaborative operation that continues working at speed around them. He says current work focuses on cooperative safety, including both hardware that senses interaction and software that interprets safe behavior. He also distinguishes robot safety from the safety of learning based AI running on robots.
Cardenas says the Mercedes work shown was an early pilot, beginning with teleoperation to learn what tasks Apollo could perform. He expects deployments to remain mostly in the pilot stage in 2026, with hundreds or early thousands of systems for most groups, and sees 2027 as a likely start of broader scaling. Apptronik is working with Google DeepMind on Apollo and Gemini, and Cardenas says data collection, including human perspective data, is a key challenge.
Cardenas says a viable application depends on the industry: robots might handle cases, manipulate objects, or transport materials. Customers need task performance that meets their KPIs, including reliability and task rate, and a positive return on investment. Apptronik favors dexterous hands for versatility and learning from human demonstrations, while weighing their cost and durability against simpler grippers.
Cardenas names lower bill of materials cost, simpler systems, and manufacturing at higher rates as hardware priorities. Apptronik has developed more than 70 distinct electric actuators, and is also working on integrating AI models onto robots. He adds fleet management and tasking as platform challenges, and says 2026 progress will shape how people judge humanoids in 2027 and beyond.
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