From LIANSHI's lawn-mowing robots to WHEELTEC's educational robots and commercial cleaning robots, Nanoradar Radar  is rapidly expanding into an increasing number of robotic applications. With advantages such as dual wide fields of view, a compact form factor, and easy integration, Nanoradar Radar continuously adapts to diverse robot platforms and scenarios, delivering reliable perception for functions like navigation and obstacle avoidance, object detection, and target tracking, and gradually becoming a standard building block within the robotics ecosystem.

Millimeter-wave radar is becoming a key sensor for robot perception. 
Outdoor vegetation and dust, indoor pedestrian traffic and low obstacles—complex environments place higher demands on the stability and coverage of a robot's perception. No single sensor can handle every scenario, making multi-sensor fusion an increasingly important trend.

Compared with LiDAR and vision, millimeter-wave radar can still reliably provide information on target distance, velocity, and bearing in conditions such as rain, fog, dust, bright light, and low light, making it an essential sensor for autonomous robotic operations.

Multi-sensor fusion to build a more reliable robotic perception system 
In robotic perception systems, millimeter-wave radar, LiDAR, and vision can work in concert: LiDAR captures spatial contours and environmental structure, vision provides object categories and semantic information, and millimeter-wave radar reliably outputs target distance, velocity, bearing, and other data.

By fusing multi-source sensory data, robots can obtain a more comprehensive understanding of their surrounding environment, providing more reliable perceptual input for functions such as navigation and obstacle avoidance, dynamic object detection, and target tracking.

Figure: Wheelchair Robot Millimeter-Wave Radar and LiDAR Fusion Perception Interface

Focusing on being integrated, becoming a “standard building block” in the robotics open-source ecosystem. 
Nanoradar's in-vehicle radar supports mainstream open-source ecosystems such as ROS/ROS2, Autoware, and Baidu Apollo, and features multiple interfaces including serial port, CAN, and RS485. Its compact, cap-sized form factor facilitates easy integration, enabling faster deployment of the radar on robotic platforms.

1. ROS/ROS2 Integration: Seamless Data Flow in the Robotics Ecosystem Nanoradar's full range of automotive radars has been adapted to ROS/ROS2, enabling radar data to be published in standard message formats. Customers can rapidly develop higher-level applications such as perception, localization, and mapping without needing to manage underlying communication protocols. 

2. APOLLO/AUTOWARE Integration: Deeply Integrated into the “Gold Standard” Autonomous Driving Development Framework Nanoradar's 4D imaging radar SR75, obstacle-avoidance radar SR73F, and dual wide-angle radar AFM711 have completed adaptation. These radars can be quickly integrated into autonomous driving perception pipelines, supporting online calibration, data visualization, and coordination with perception, prediction, planning, and other modules.