Smart Software Detects Glass Walls with 96% Accuracy—No Expensive Sensors Needed

Researchers at South Korea’s Daegu Gyeongbuk Institute of Science and Technology (DGIST) have developed a software-based solution that enables low-cost LiDAR sensors to detect transparent obstacles like glass walls with 96.77% accuracy. This innovation offers a cost-effective alternative to expensive high-resolution sensors typically required for such detection.

Autonomous robots often rely on LiDAR sensors to navigate their environments. However, affordable LiDAR systems struggle to detect transparent materials, mistaking them for empty space and risking collisions. High-end sensors can overcome this issue but are prohibitively expensive, increasing system costs significantly.

The DGIST team, led by Professor Kyungjoon Park, introduced the Probabilistic Incremental Navigation-based Mapping (PINMAP) algorithm. PINMAP enhances the capabilities of existing low-cost LiDAR sensors by accumulating and analyzing sparse data points to probabilistically identify the presence of glass walls over time. Built upon open-source tools like Cartographer and Nav2 within the ROS 2 ecosystem, PINMAP can be integrated into current systems without hardware modifications.

In practical tests, PINMAP-equipped robots achieved a 96.77% success rate in detecting glass walls, a significant improvement over the near-zero detection rate of traditional methods using the same sensors. This advancement demonstrates that software enhancements can substantially improve sensor performance, offering a scalable and economical solution for safer indoor navigation in environments such as hospitals, offices, and warehouses.