The HONOR Robotics D1 is a Humanoid humanoid robot developed by HONOR Device Co., Ltd.. The HONOR Robotics D1 is unknown.
Primary use case: Humanoid locomotion demonstration — reported as the first robot to break the human half-marathon limit
Locomotion
bipedal
Hand Type
unknown
Autonomy Level
unknown
Availability
unknown
Primary Use Case
Humanoid locomotion demonstration — reported as the first robot to break the human half-marathon limit
Xiaomi developed a 324-gram, 21-DoF bionic hand with 26 motors, roughly 1,500 tactile points, and forearm-mounted tendon actuation, grounding its design in 1,827 automotive-factory SOPs rather than generic dexterity benchmarks. Xiaomi's analysis reported substantially better stable-grasp performance than simpler 6-to-15-DoF manipulators, but the hand remains undeployed and lacks public pricing, availability, independent reliability testing, and a security audit. The article also warns that Chinese intelligence and data-security laws, along with U.S. restrictions on foreign robotic devices, could prevent Western automotive manufacturers from adopting it.
Researchers at UCLA have developed PhoneBot, an open-source small humanoid robot that uses a low-cost Android smartphone (replacing dedicated cameras, sensors and computing hardware) as its eyes, sensors and main processor. The 48.3 cm, 1.8 kg, 13-servo robot costs about $400 for hardware excluding the phone, which adds $50–$80, and was tested with four Android phones including the 2017 Honor 9. Capabilities demonstrated include walking, recovering from falls, and visually tracking people, though limits remain in payload, dynamic motion, uneven terrain and manipulation due to its low-power servos and armless design.
UCLA researchers have built PhoneBot, an open-source humanoid robot that repurposes cheap Android smartphones (including a 2017 Honor 9 and devices costing $50–$80) for vision, motion sensing, and on-device locomotion control via TensorFlow Lite. Standing 483 mm tall, weighing 1.8 kg, and using 13 servo motors plus a rotating torso, the platform is built from roughly $400 in non-phone hardware, with walking control trained via reinforcement learning using mirrored samples to improve gait symmetry.