The advent of inexpensive digital cameras with depth sensing capabilities (RGB-D cameras) has opened the door to numerous useful applications that need quantitative measures of dynamic fields whose simultaneous time history quantification (at many points as dictated by the resolution of the camera) provides capabilities that were previously accessible only through expensive sensors (e.g., laser scanners). This paper presents a comprehensive experimental and computational study to evaluate the performance envelope of a representative RGB-D sensor (the first generation of Kinect sensor) with the aim of assessing its suitability for the class of problems encountered in the structural dynamics field, where reasonably accurate information of evolving displacement fields (as opposed to few discrete locations) that have simultaneous dynamic planar translational motion with significant rotational (torsional) components. This study investigated the influence of key system parameters of concern in selecting an appropriate sensor for such structural dynamic applications, such as amplitude range, spectral content of the dynamic displacements, location and orientation of sensors relative to target structure, fusing of measurements from multiple sensors, sensor noise effects, rolling-shutter effects, etc. The calibration results show that if the observed displacement field generates discrete (pixel) sensor measurements with sufficient resolution (observed displacements more than 10 mm) beyond the sensor noise floor, then the subject sensors can typically provide reasonable accuracy for transnational motion (about 5%) when the frequency range of the evolving field is within about 10 Hz. However, the expected error for torsional measurements is around 6% for static motion and 10% for dynamic rotation for measurements greater than 5°.

Autonomous monitoring of infrastructure systems offers a promising alternative to manual inspection techniques which are mostly tedious, expensive and prone to error. Robot-based autonomous monitoring systems not only provide higher precision, but they also allow frequent inspection of infrastructure systems at a much lower cost. Recent advancements in robotic systems have led to the development of reconfigurable swarm robots (RSR) that can change their shape and functionality dynamically, without any external intervention. RSR have the advantages of being modular, on-site reconfigurable, multifunctional, incrementally assemble-able, reusable, faulttolerant, and even repairable on the orbit. Newly-developed reconfigurable robots are expected to bring a radical change in the prevailing structural health monitoring techniques, thus augmenting the efficiency, accuracy and affordability of inspection operations. This paper presents a holistic review of the previous studies and state-of-the-art technologies in the field of RSR, and argues that RSR offer great potential advantages from the perspective of monitoring and assessment of civil and mechanical systems. A roadmap for future research has also been outlined based on the limitations of the current methods and anticipated needs of future inspection systems.