Affordable bimanual robot for day-to-day home tasks, with 7+1-DOF arms rated for 1.5 kg payload per arm, lidar, four 720p RGB cameras, audio, and 6–8 hours of battery life.
Primary use case: Day-to-day home tasks
DOF
8
Payload
1.5 kg
Battery
6 hrs
Price
$2K
Degrees of Freedom
8
Locomotion
unknown
Hand Type
Grippers
Payload
1.5 kg
Max Lift/Arm
1.5 kg
Battery Life
6 hrs
Autonomy Level
unknown
AI Capabilities
Task training at home via the Nori Lab app, Skill sharing through the Skills Marketplace, Spoken command interaction
Price
$2K
Availability
Pre-order now; ships Fall 2026
Primary Use Case
Day-to-day home tasks
OpenAI's GPT-6 Astra achieved 95% success on gross pick-and-place tasks in independent testing by RoboCurve, completing runs at $0.94 with 6.2x less token usage than Claude Fable 5.1, but stalled at just 10% on sub-millimeter precision insertion tasks. The benchmark highlights rapid progress in LLM-driven kinematics while exposing persistent challenges in physical contact dynamics that require tactile feedback and compliance to solve.
ABSTRACT There is great interest in alternative pollination strategies for crop production in the face of climate change and perennial threats to the traditional pollination mechanisms. This review explores the potential of robotic pollination as a promising solution to these challenges affecting crop fertilization, agricultural sustainability, and global food production. We comprehensively examine recent advances in robotic pollination systems that integrate artificial intelligence, machine vision, robotics, and precision sensing to supplement or complement conventional insect-me
Nori Robotics, a five-person San Francisco startup emerging from Y Combinator's Summer 2026 cohort, has launched the Nori A3, a 19-DoF wheeled bimanual mobile manipulator priced at $1,688—positioning it as an ultra-low-cost developer platform rather than a turn-key household assistant. The robot features a Raspberry Pi 5 compute architecture and 3D-printed TPU grippers to achieve its price point, with transparent engineering documentation acknowledging early-stage perception and navigation limitations.