I. Requirements Analysis:

Digital transformation has been incorporated into China's 14th Five-Year Plan and the long-term goals for 2035. As the new round of technological revolution and industrial transformation deepens, digitalization and intelligentization have become new engines driving high-quality industrial development. As critical infrastructure, the stable operation of power facilities such as substations is paramount to social and economic progress. Power substation inspections are highly repetitive and labor-intensive, often conducted in complex terrain. Most domestic substations rely on traditional manual patrols, which are constrained by factors such as inspectors' skill levels and experience. This leads to frequent instances of missed inspections, misidentifications, and undetected defects, ultimately causing circuit failures. Manual inspections struggle to fully meet the safety requirements of modern substations. Meanwhile, traditional power inspection robots are predominantly wheeled, limiting their ability to operate continuously across irregular terrains such as multi-level structures, stairs, grassy areas, and muddy surfaces.

II. Working Principle

The intelligent quadrupedal robot, as an intelligent device integrating locomotion capabilities such as walking, running, jumping, and recovering from falls, has demonstrated high adaptability to unstructured outdoor terrain in substations—including pebbles, grassy areas, and steep slopes—without altering the original environment. It has also successfully navigated various obstacles at boundary points, such as steps and staircases, achieving comprehensive coverage across all scenarios for inspection robots within substations.

III. Features and Functions

Full-scenario coverage will enable more efficient power inspections for electrical systems:

1. Significantly expand robotic inspection coverage: Quadruped robots can cover substations spanning 25,000 square meters.

2. Bridging outdoor and indoor inspection scenarios: Previously, separate robots were required for outdoor and indoor environments in substations. Quadrupedal robots can navigate diverse terrains both indoors and outdoors while overcoming boundary obstacles, thereby reducing inspection costs and enhancing management efficiency.

3. Enhanced Inspection Efficiency and Data Quality: Compared to traditional wheeled robots, quadrupedal robots can traverse obstacles, shorten inspection routes, and select more optimal observation positions. Omnidirectional autonomous navigation, intelligent recognition, smart inspection; utilizing SLAM (Simultaneous Localization and Mapping) based on LiDAR, the quadrupedal robot achieves model-free point cloud mapping in substations. It collects 3D point cloud data within a 25,000-square-meter substation in approximately 20 minutes, autonomously plans omnidirectional navigation paths according to task models, and reports coordinate information in real time. The quadruped robot's AI computing power enables on-site target detection in a small closed-loop system, tolerating deviations caused by environmental disturbances. Deep learning-based algorithm models achieve target status recognition and temperature detection.

IV. Product Specifications

Serial Number	Category	Name	Technical Specifications
1	Entity size	Dimensions when laid flat (Length × Width × Height)	1070mm×470mm×346mm
		Dimensions when standing(Length × Width × Height)	950mm×470mm×700mm
		Total weight	53kg
2	Electrical Parameters	Battery capacity	19.5Ah (ideal data measured at 25°C ambient temperature)
		Battery rated voltage	72V
		No-load operating time	4h
		Payload endurance time	2h
		Charger Input	200V~240V
		Charger Output	84V/8A
		Charging duration	11 p.m. to 3 a.m.
		External Power Supply Connector	5V; 12V; 24V; 72V(BAT)
		External Communication Interface	Ethernet; WiFi; USB; RS485/RS232
		Autonomous Charging Function (Optional)	Support
3	Motion Parameters	Maximum speed	4.95 m/s (maximum test data)
		Maximum walking speed	1.7 m/s
		Maximum climbable slope gradient	±30°
		Maximum climbable step height	18cm
		payload	20kg
		Maximum load	85kg (maximum load test data)