PaceRobotics®
Website:
pacerobotics.net
Job details:
About the Role:
We are seeking a high-caliber Post-Graduate to join our Robot Autonomy team in Bengaluru. This is an intensive 6-month residency designed for engineers with a Master’s degree who excel at applying first-principles physics to complex robotic challenges. You will be responsible for building highly accurate and precise localization and mapping stack for our autonomous systems that will reliably help them navigate and plan their work in ever changing construction environments.
Key Responsibilities:
- State Estimation: Develop and fuse multi-sensor pipelines (3D LiDAR, IMU, Wheel Odometry) using Factor Graphs, EKF etc. to provide a stable pose estimate at 100Hz+.
- Point Cloud Registration: Implement and optimize scan-matching algorithms (ICP, NDT, or Feature-based) robust to dusty environments and feature-poor hallways.
- Loop Closure & Optimization: Design robust loop closure detection to eliminate long-term drift, ensuring the robot can return to its homing position after a full-floor mission.
- Life-Long Mapping: Implement "Map Cleaning" or sub-mapping techniques to handle construction sites where geometry changes daily.
- Manual Data Pipeline: Manage a data pipeline to build a local dataset of site geometries for off-site training and simulation.
- Leverage latest Deep Learning/Machine Learning based techniques to develop robot’s decision making capabilities.
- Collaborate closely with hardware teams to deploy solutions on physical robots.
- Contribute to technical research and stay updated with the latest in 3D Robot Vision and SLAM literature.
- Perform debugging, profiling and performance tuning for on-robot deployment.
Technical Requirements & Qualifications:
- A Master's degree in a relevant field like Robotics, Control Systems, Mathematics, Computer Science, Electrical Engineering etc.
- Strong understanding of SLAM concepts (Graph-based SLAM, Visual SLAM, LiDAR SLAM, etc.)
- Proficient in sensor fusion using Kalman Filters, Particle Filters, or other probabilistic models.
- Familiarity with classical Computer Vision techniques
- Familiarity with concepts related to ML/DL
- Good programming skills in C++ and Python
- Experience with ROS and/or ROS 2
- Experience with deep learning-based localization or VO/VIO systems.
- Strong foundations in mathematical concepts of Linear Algebra, Probability, Statistics and Differential Calculus
- Experience with simulation environments like Gazebo Ignition, ISAAC sim etc.
- Experience with implementing robot software on NVIDIA Jetson based Edge Computing devices
- Familiarity with relevant Libraries: PyTorch, TensorRT, ONNX, Eigen, Open CV, PCL, Open3D, Ceres etc.
- Hands-on experience with real robots and perception sensors such as time-of-flight and stereo cameras, 2D/3D LIDAR, and IMUs.
- Comfortable with Git and collaborative development workflows.
- Comfortable with Digital SIgnal Processing and Robot Kinematics
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