Quadcopter LIO Consultant

🤖 About Us

We build robots that operate where no other robots can.

Born out of NASA JPL's work on the DARPA Subterranean Challenge, Revolute Robotics is redefining where inspection and surveillance robots can access. Our mission is to keep humans out of harm’s way using an entirely new class of robots—enabling safer, smarter data collection for industrial inspections, area surveillance, and first responders.

We’re gearing up for field pilots with major industrial customers, we’re backed by NSF, DoD, and top VCs, and are 1 of 10 companies selected to spend a week with Jeff Bezos at MARS 2024.

⚙️ The Role

We’re looking for a Controls / Autonomy Engineer to help us achieve stable flight in dark, dirty, GPS-denied confined spaces. We’re looking for someone with deep, hands-on experience implementing LIO frameworks on drones inside the aforementioned environments.

The consultant will work remotely (or in-person, if/when possible) to guide, troubleshoot, debug, and help integrate LIO for position hold and collision avoidance. The role requires close collaboration with our in-house engineering team to provide step-by-step guidance, log analysis, code changes, and remote debugging.

🔍 Key Responsibilities

• Integrate and adapt LIO pipelines (e.g., LIO-SAM / FAST-LIO / COIN-LIO) for 3D LiDAR on a quadcopter platform.
• Provide support to our engineering team for troubleshooting and debugging LIO frameworks and LiDAR-IMU integration.
• Analyze flight and sensor logs, diagnose failures, and recommend/tailor fixes (tuning, syncing, filtering). Provide help debugging the closed-loop system of both LIO and quadcopter. 
• Review and contribute ROS code to submit small patches and perform code reviews.
• Design and validate real-time motion planning and collision avoidance approaches that use LIO output and LiDAR data.

⚠️ Required Qualifications

• Minimum 1 year of hands-on LIO experience on UAS in GPS-denied spaces. 
• Practical experience with LiDAR-inertial fusion, time synchronization, latency troubleshooting, time-of-flight and optical flow sensors, and low-res LiDAR adaptation.
• Strong ROS experience and ability to produce maintainable C++ code
• Experience integrating SLAM outputs with autopilots (PX4 / ArduPilot / MAVROS) and motion planners.
• Demonstrated ability to work remotely, explain technical issues clearly, and guide engineers through step-by-step fixes.

⭐ Preferred Qualifications

• Boston-area candidate (for optional on-site tests), but remote candidates welcome.
• Public repos, demo videos, flight logs, or publications demonstrating relevant LIO/quad work.
• Experience optimizing performance for low compute/low-resolution sensors.