Project Overview

This project involves the deployment of a fleet of 5 autonomous robots equipped with a comprehensive sensor suite including RGB cameras, LiDAR, and IMUs. The goal was to collect a large-scale, synchronized dataset to benchmark various SLAM (Simultaneous Localization and Mapping) algorithms in real-world environments.

Key Achievements

• Large-Scale Data Collection: Successfully collected and synchronized over 1TB of multi-modal sensor data.
• Multi-Robot Coordination: Managed the simultaneous operation of multiple robots to cover extensive areas efficiently.
• SLAM Benchmarking: The dataset serves as a rigorous benchmark for evaluating the performance and robustness of state-of-the-art SLAM algorithms.