SLAM Engineer

Job Title: SLAM engineer

Job Type: Full Time, WFO, 5 Days Week

Work Location: Bharat Forge, Mundhwa, Pune

Experience: 1-3 yrs

Job Overview

We are seeking a highly skilled Robotics Engineer specializing in Simultaneous Localization and Mapping (SLAM) and Navigation for humanoid robotics. This role requires deep expertise in ROS2, advanced motion planning, and sensor fusion, with a particular focus on 2D & 3D non-odometric SLAM methods, including RTAB-Map, ORB-SLAM, LIO-SAM, LOAM, and ICP-based techniques.

Key Responsibilities:

Robotic Software Development:

Design and optimize scalable ROS2-based robotic applications ensuring high-performance system execution.

Develop ROS2 nodes, services, clients, and publishers/subscribers for seamless data exchange in robotic systems.

SLAM & Sensor Integration:

Implement 2D & 3D SLAM techniques including RTAB-Map, ORB-SLAM, LIO-SAM, LOAM, ICP, enabling high-precision mapping and localization.

Integrate multi-sensor fusion using LiDAR, GPS, IMU, Stereo & Depth Cameras, Radar, ensuring robust autonomous navigation capabilities.

Optimize SLAM-based real-time pose estimation, enabling humanoid robots to function in low-feature, dynamic environments.

Motion Planning & Control:

Develop path planning and trajectory optimization algorithms for adaptive humanoid mobility.

Implement navigation controllers, including PID, EKF, MPC, and SMAC, ensuring smooth and reactive control tuning.

Work with behavior-based AI-driven planning frameworks for dynamic obstacle avoidance and self-learning navigation strategies.

URDF Modelling & Simulation:

Develop and optimize URDF models, accurately representing humanoid robot kinematics and physical configurations.

Utilize Gazebo, Rviz2, Unity, and Omniverse for simulation-based testing and validation.

Advanced SLAM & Localization:

Work on Sim2Real adaptation, ensuring optimized SLAM models translate effectively into real-world humanoid robotics applications.

Develop probabilistic localization models, ensuring precise sensor-based real-time mapping and decision-making.

Documentation & R&D:

Maintain technical documentation for SLAM architectures, motion planning algorithms, and system integration workflows.

Stay updated with latest advancements in robotics, AI-driven navigation, and deep learning applications for autonomous humanoid mobility.

Required Skills & Experience

Expertise in ROS2, SLAM (RTAB-Map, ORB-SLAM, LIO-SAM, LOAM, ICP), and advanced navigation algorithms.

Hands-on experience with sensor fusion, including LiDAR, GPS, Radar, Cameras, IMU.

Strong knowledge of inverse kinematics, PID controllers, EKF-based localization & MPC control tuning.

Proficiency in Gazebo, Rviz2, Simulink, Orocos, Mujoco, Isaac Sim, Omniverse, NVIDIA ecosystem tools.

Experience working with humanoid or legged robotic systems in real-world deployment scenarios.