LumiBot Showcases Dexterous Hands and Manipulation Foundation Models at IROS 2026

LumiBot, known in China as Shiyue Technology, is showcasing its latest finger-shaped visuo-tactile sensors, dexterous hand series, and manipulation foundation models at IROS 2026. The startup, founded just over a year ago, has also been selected as a high-potential startup to present at the official IROS Startup Session.

At the heart of LumiBot's showcase is a core thesis: the upper bound of data quality is strictly determined by hardware reliability. In embodied AI, high-quality real-world manipulation data remains critically scarce. Industry-wide, public multimodal datasets featuring high-DOF dexterous hands with tactile feedback total only a few tens of thousands of samples, whereas training scalable manipulation models requires tens of millions of hours of real-world operational data. LumiBot tackles this bottleneck at the hardware source by utilizing highly reliable, high-precision hands and visuo-tactile sensors to ensure collected data is standardized, clean, and reusable from day one.

The Lumi-Dex hand series supports mainstream industrial communication protocols and integrates across various robotic arm platforms and simulation environments, serving as a unified execution endpoint for diverse embodied architectures. On-site, LumiBot is demonstrating its high-DOF hands, notably the Lumi-Dex-21, which features an innovative drive-control integrated design combining linkage and direct-drive mechanisms. The company's upcoming flagship dexterous hand brings upgrades in lifespan, durability, and thermal management, powered by a self-developed active-cooling micro joint module that maintains operating temperatures around 50°C and supports over 5,000 hours of continuous no-load operation.

The Lumi-Tac visuo-tactile sensor V2 incorporates structural and optical optimizations over its predecessor, extending coverage across the fingertip, finger side, and finger pad with enhanced wear resistance and deformation reliability. Key specifications include a 10-micron spatial resolution, 0.02 N force detection accuracy, and a 120 fps frame rate. Paired with proprietary high-precision curved surface reconstruction algorithms, Lumi-Tac delivers comprehensive multimodal tactile capture for model training.

On the data front, LumiBot has operationalized its real-robot teleoperation collection pipeline for continuous data gathering. Its egocentric data-to-robot mapping scheme has achieved millimeter-level precision verification. The Lumi-Mind manipulation foundation model utilizes a hierarchical MoT architecture that deeply fuses Vision, Tactile, Language, and Action modalities. Through a unique memory mechanism and tactile gating, Lumi-Mind enables long-horizon task planning and fine-grained micro-adjustments during dense contact. Via its proprietary Lumi-Cap data pipeline, LumiBot connects Ego video capture, teleoperation data gathering, and automated data cleaning into a capture-train-deploy-feedback flywheel.

At IROS, LumiBot demonstrated its self-developed Lumi-Dex-11 lower-DOF hand driven by the Lumi-Mind model as it executed a complex sequence: picking up a stamp, precise stamping, picking up a tray, handing out a card, returning the tray, and returning the stamp. When human disturbances were introduced, the model autonomously re-evaluated and adjusted its task planning in real time.

Founded in 2025, LumiBot has developed its entire product portfolio in-house, spanning motors, visuo-tactile sensors, complete dexterous hands, manipulation models, and data acquisition pipelines. The company is advancing scenario validation and technical verification with industry leaders across automotive manufacturing, 3C electronics, and life sciences.