Role Overview
We are looking for a Robotic Software Engineer specializing in SLAM, point cloud processing, and high-density map generation for autonomous robotic applications. The ideal candidate will have expertise in robotic perception, image processing, and real-time SLAM algorithms, contributing to the development of robust navigation and mapping solutions.
Key Responsibilities
- Develop and optimize SLAM algorithms (LiDAR, Visual, RGB-D, or Multi-Sensor Fusion) for real-time applications.
- Implement point cloud processing pipelines for noise filtering, segmentation, and high-density map generation.
- Work with image processing and deep learning techniques for feature extraction, obstacle detection, colorization, and enhancement of point clouds.
- Integrate multi-sensor fusion using LiDAR, cameras, IMUs, and/or GPS for robust localization and mapping
Requirements
- Bachelor’s, Master’s, or PhD in Robotics, Computer Science, Electrical Engineering, or a related field.
- Strong background in Simultaneous Localization and Mapping (SLAM), including both LiDAR-based and vision-based SLAM.
- Experience with point cloud post-processing techniques, including noise filtering, downsampling, and surface reconstruction.
- Proficiency in high-density point cloud colorization using RGB-D cameras, multi-sensor fusion, or deep learning techniques.
- Experience with map generation techniques for robot navigation and environment reconstruction.
- Solid understanding of computer vision and image processing techniques.
Technical Skills
- Programming: Proficiency in C++ and Python for robotic perception and processing pipelines.
- Frameworks & Libraries:
- SLAM & Mapping: LIO based SLAMs
- Point Cloud Processing: PCL (Point Cloud Library), Open3D.
- Image Processing & Deep Learning: OpenCV, PyTorch, TensorFlow.
- Robotics & Simulation: ROS 1/2, Gazebo, RViz.