At the India AI Impact Summit 2026 in New Delhi, Qualcomm highlighted its growing robotics ambitions by showcasing AI-driven humanoid robots and its complete robotics technology stack. The platform, which made its Indian debut at the summit, was first introduced earlier this year at the Consumer Electronics Show. The company presented what it described as a full end-to-end robotics solution that integrates hardware, software and artificial intelligence.
According to Qualcomm, the platform is built to accelerate the rollout of “physical AI” systems. These systems include household robots, industrial autonomous mobile robots (AMRs) and full-sized humanoid robots. The focus is on enabling faster deployment while maintaining performance and efficiency across different environments and use cases.
A major highlight of the showcase was the new Dragonwing IQ-10 processor, Qualcomm’s first chip designed specifically for robotics. The processor is built to power full-sized humanoid robots as well as advanced AMRs used in factories and warehouses. The company said the chip can manage complex robotics tasks while remaining energy efficient. It also serves as the foundation of Qualcomm’s broader robotics architecture, allowing developers to scale performance based on different robot designs and operational needs.
During a live demonstration featuring a humanoid robot, Qualcomm detailed its general-purpose robotics architecture. The system combines edge computing, machine learning tools, software frameworks and what it called an AI data flywheel. This approach is designed to help robots learn continuously and improve over time. With integrated vision, audio and motion capabilities, robots can adapt to new environments and perform real-world tasks more effectively. Qualcomm said its modular design makes industrial deployment simpler while maintaining reliability and industry standards. Instead of addressing every possible use case, the company is currently focusing on 10 priority tasks across logistics, manufacturing and retail. These include item picking, case stacking, line sequencing and inventory scanning. Qualcomm believes targeting high-demand automation tasks will speed up commercial adoption. The strategy also builds on its experience in multi-criticality AI systems developed for Advanced Driver Assistance Systems (ADAS).
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