The engineers behind Forge Robotics

Bilal Rehman

Autonomy, Mapping & Localisation Lead

Bilal is a robotics autonomy specialist focused on helping robots understand their surroundings, maintain reliable positioning and operate safely in real-world environments.

He brings more than seven years of robotics research and production experience across SLAM, mapping, localisation, state estimation, multi-sensor fusion and autonomous-system deployment. He currently leads SLAM and localisation work for production autonomous service robots operating internationally.

His work includes combining camera, LiDAR and IMU data into robust mapping and localisation pipelines, designing calibration workflows, improving robot pose estimation, maintaining maps over time and diagnosing failures when robots operate in changing customer environments.

Bilal has also developed ROS 2 integration patterns around the Unitree Go2 SDK in simulation, including DDS communication, state and command bridging, telemetry, visualisation, keyboard teleoperation and safety-oriented posture services. His strength is not simply building a demo, but creating the localisation, sensor and diagnostic foundations that allow a robot to operate more reliably over time.

At Forge Robotics, Bilal’s capability is particularly relevant to customer-site trials where robots need to map an unfamiliar environment, maintain position indoors without GPS, detect when localisation confidence drops, recover from map changes and provide useful monitoring data to technical teams.

Hamza is a robotics engineer specialising in deploying, testing and improving autonomous mobile robots in real operational environments.

His experience covers warehouse robotics, mobile manipulation, robot perception, ROS 2 software, sensor integration, customer-site testing and technical diagnosis. He has worked on production robotic platforms designed for warehouse logistics, including pallet handling, small-load-carrier handling and autonomous picking workflows.

Hamza has practical experience developing robot behaviours, camera and perception utilities, RGB-D segmentation pipelines, robot testing workflows and simulation-backed CI/CD environments. He has also supported large customer deployments, using logs, ROS bags, video and remote diagnostics to identify faults caused by hardware issues, lighting, calibration, environment setup, navigation problems and machine-learning edge cases.

His work is particularly relevant to Forge Robotics because successful robot projects depend on more than proving a task once. They require reliable operation in changing workplaces, clear diagnostic processes, repeatable testing and a practical understanding of what causes robots to fail outside the lab.

At Forge Robotics, Hamza’s capability is especially relevant to warehouse, logistics, manufacturing and mobile-robot trials where robots need to navigate, detect objects, manipulate loads, recover from faults and be refined through real customer-site testing.

Mateo Kovačević

Robotics Integration & Field Deployment Lead

Mateo is a robotics engineer specialising in taking advanced autonomous systems from development into safe, repeatable real-world operation.

His experience spans ROS and ROS 2 robotics, autonomous navigation, sensor integration, robot SDK/API integration, remote diagnostics and controlled field deployment. He has worked across UAV, mobile robotics and autonomy systems, combining software, perception hardware, safety procedures and live operational testing.

He has practical experience integrating MAVLink and MAVROS with ArduPilot and PX4 flight-control platforms, together with RealSense stereo cameras, Velodyne, Ouster and RoboSense LiDAR systems, Gremsy gimbals and Sony camera SDKs. He has built ROS wrappers around proprietary hardware interfaces so that complex equipment can be controlled and monitored through robust, reusable robotics workflows.

His work includes autonomous wind-turbine inspection, where he was responsible for real-hardware integration, field validation, safety procedures, failsafes, pre-flight checks and remote diagnosis through logs and SSH access.

At Forge Robotics, his capability is particularly relevant to assessing new robot platforms, understanding manufacturer SDKs, connecting sensors and control systems, creating reliable ROS 2 integration layers, establishing safe testing procedures and supporting pilots as they move from simulation into real operating environments.

Aditya Kulkarni

Robotics Perception & Autonomous Systems Engineer

Aditya is a robotics and autonomous-systems engineer specialising in perception, localisation, sensor fusion and real-world robotic data pipelines.

His experience combines advanced robotics with autonomous-vehicle engineering, including ROS 2, multi-camera systems, LiDAR, IMU data, sensor calibration, edge AI and high-performance inference on NVIDIA platforms.

Aditya has worked directly with a physical Unitree Go2 EDU quadruped robot, supporting LiDAR SLAM, sensor data capture, logging and motion-prediction workflows within a ROS 2-based environment. His work included creating and validating data pipelines from the physical robot, integrating localisation outputs and producing predicted future-pose information for downstream planning and locomotion systems.

Alongside robotics work, Aditya has experience in autonomous-driving development environments involving vehicle-mounted cameras, LiDAR, IMU, CAN data, perception models and real-time deployment hardware. This gives him a strong understanding of how perception systems must perform outside a controlled lab environment, where sensor quality, timing, calibration and reliable data flow all matter.

At Forge Robotics, Aditya’s capability is particularly relevant to quadruped and mobile-robot sensing, localisation, SLAM, camera and LiDAR integration, operational data capture, mapping, obstacle awareness and the perception layer required for robots to operate more intelligently in real environments.