Robotic Systems for Power Substation Inspection
Summary
Power substations represent critical nodes in electrical grids where high-voltage equipment and control systems converge. Inspection of these facilities has traditionally relied on manual tours, exposing personnel to hazards such as electric arcs, moving machinery and confined spaces. Robotic systems are transforming this landscape by integrating autonomous navigation, advanced sensing and specialised diagnostic modules to conduct detailed examinations of switchgears, busbars and transformer assemblies. Wheeled and tracked platforms navigate both indoor and outdoor environments using simultaneous localisation and mapping (SLAM), aided by LiDAR, depth cameras and GNSS. Unmanned aerial vehicles augment ground units by accessing overhead structures and thermal anomalies. Multi-spectral cameras and partial discharge sensors detect insulation degradation, hotspots and corona discharge activity without interrupting live operations. Modern inspection robots leverage machine learning for image analysis, enabling rapid identification of defects and prognostic maintenance recommendations. The adoption of these systems enhances safety, reduces downtime and delivers real-time condition assessments across distributed networks. As global grid infrastructure ages and renewable generation expands, the scalability and adaptability of robotic inspections become paramount to ensure reliability and compliance with stringent operational standards.
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Robotic Systems for Power Substation Inspection publication trend
The graph below shows the total number of articles in robotic systems for power substation inspection across all publications each year (not limited to Nature Index journals).
Technical terms
Simultaneous Localisation and Mapping (SLAM): A computational technique allowing a robot to build a map of an unknown environment while tracking its own position.
Global Navigation Satellite System (GNSS): Satellite-based technology providing geospatial positioning for outdoor navigation and targeting.
Extended Kalman Filter (EKF): An algorithm that fuses noisy sensor data to estimate a system’s state, such as a robot’s pose and velocity.
A* Algorithm: A heuristic search method for finding the shortest path between two points in a grid or graph, balancing cost and distance.
Dynamic Window Approach (DWA): A real-time local path planning technique that selects feasible velocities to avoid obstacles based on the robot’s dynamic constraints.
References
- GNSS-Based Narrow-Angle UV Camera Targeting: Case Study of a Low-Cost MAD Robot. Sensors (2024).
- SLAM, Path Planning Algorithm and Application Research of an Indoor Substation Wheeled Robot Navigation System. Electronics (2022).
- Advancements in Substation Inspection Robots: A Review of Research and Development. E3S Web of Conferences (2024).
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