Own SLAM and localization that keep our platforms oriented in corridors, fairways, home pools, and industrial spaces — building on mobile-robot mapping DNA.

Responsibilities

Develop and maintain SLAM / localization (visual, LiDAR, or multi-sensor) for indoor / outdoor platforms
Improve mapping quality, loop closure, relocalization, and long-term map maintenance
Work with planning & control on odometry quality, free-space, and failure recovery
Integrate IMU, wheel odometry, TOF / array LiDAR, and cameras into robust state estimation
Benchmark on real robots; diagnose drift, outliers, and degenerate scenes

Requirements

Bachelor’s or above in robotics, CS, automation, or related; 2+ years SLAM / localization preferred
Strong C++ and numerical methods; familiar with ROS / ROS2 or equivalent
Solid understanding of filtering / optimization (EKF / factor graph / BA)
Hands-on with LiDAR or visual SLAM frameworks (e.g. LOAM-family, ORB-SLAM, Cartographer, or similar)
Ability to ship algorithms that run stably on resource-constrained devices

Nice to have

Multi-floor / large-scale mapping; semantic SLAM
Experience from AGV, AMR, or robot-vacuum navigation teams
GPU / DSP acceleration for perception front-ends

How to apply

Email qianeasy@qianeasy.com with subject SLAM Algorithm Engineer.