Hefei Team Builds Forestry Inspection Robot for All-Weather Fire Detection

Forest fire prevention has long relied on three approaches: fixed sensors, manual patrols, and conventional smart devices. After surveying multiple forest regions across China, Cheng Ziyang's team found that each approach carries distinct limitations.

Fixed sensors are expensive to deploy and leave large coverage blind spots. Manual patrols suffer from low efficiency and high risk. Traditional intelligent equipment is slow to recognize threats and weak in autonomous capability.

Hefei Fengkan Intelligent Technology developed a forestry inspection robot specifically for these pain points. The goal is to create intelligent equipment that can truly go deep into forest areas and replace manual labor for all-weather inspection. That positioning matters because forest fire prevention is not a single-technology problem; it requires sensing, mobility, and autonomous decision-making to work together in remote and unpredictable terrain. The robot targets three pain points at once: deployment cost, patrol risk, and weak autonomy in existing devices.

The team developed a control system for a forest inspection robot that fuses lidar and thermal imaging. Lidar handles three-dimensional spatial perception, while thermal imaging detects temperature. Combined, the robot no longer depends on visible light, opening inspection capabilities at night and in smoke-filled environments.

This fusion addresses a practical problem in forest fire prevention. Early-stage fires often produce no open flame, only abnormal temperature. Visible-light cameras may miss such signs, but thermal imaging can capture them.

Lidar supplies terrain and obstacle information, enabling autonomous movement in complex environments such as mountains and woodlands. The underlying control hardware uses STM32, supporting four-wheel independent drive and in-place turning.

In-place turning is critical on narrow forest roads and complex terrain. The robot does not need a large-radius U-turn and can adjust direction on the spot when it encounters an obstacle. That capability supports stable operation in spaces where conventional vehicles would struggle to maneuver. The design aims to bypass lighting limitations rather than simply adding more cameras.