Review of Robotic Systems for Aircraft Inspection

Advancements in Learning-Based Navigation Systems for Robotic Applications in MRO Hangar: Review

“…Different machine-learning-based functionalities have been developed, leveraging environmental information for robotic applications [ 28 ]. These have been demonstrated through various robotic platforms, such as the human-like robots from Boston Dynamics, the Crawling inspection robot by Cranfield University [ 2 ], and others. These robot systems follow standard robot architecture comprising sensory data acquisition, environmental perception, decision-making process, and execution of actions.…”

“…Mobile robots encompass comprehensive system structures that work together through perception, detection, motion planning, and control, as illustrated in Figure 4 , to perform a series of navigation tasks. Robotic scientists in this field have proposed many intelligent technologies integrated to form an Internet of robotic things (IORT) that can interact with the environment and learn from sensor information or real-time observation without the need for human intervention [ 2 ]. This technology empowers robots to operate more independently and make decisions based on the information they gather from their environments.…”

“…This technology empowers robots to operate more independently and make decisions based on the information they gather from their environments. Machine learning (ML) is an artificial intelligence approach that is at the core of these enabling intelligent technologies with widespread adoption [ 2 ] and has become an essential component in accomplishing many intelligent tasks in robotics. The ML techniques incorporate sensor information fusion, object detection [ 48 ], collision avoidance mechanism [ 49 ], pathfinding [ 50 ], path tracking [ 51 ], and control systems [ 21 ] to solve robot autonomous navigation problems [ 52 ].…”

“…This focus is driven by a commitment to safety and the goal to reduce operational costs, which currently represent 10–15% of airlines’ operational costs and are projected to rise from $67.6 billion in 2016 to $100.6 billion in 2026 [ 1 ]. This has heightened interest in automated visual aircraft inspection with the aim of reducing conventional assessment strategies conducted by human operators, which are often time-intensive and susceptible to transcriptional error, especially when accessing complex and hazardous areas within the aircraft [ 2 ]. To overcome these limitations and improve the effectiveness of the aircraft visual inspection process, the aerospace industry is actively exploring the integration of unmanned robotic systems, including mobile robots and drones.…”