This paper presents a robotic system using Unmanned Aerial Vehicles (UAVs) for bridge-inspection tasks that require physical contact between the aerial platform and the bridge surfaces, such as beam-deflection analysis or measuring crack depth with an ultrasonic sensor. The proposed system takes advantage of the aerodynamic ceiling effect that arises when the multirotor gets close to the bridge surface. Moreover, this paper describes how a UAV can be used as a sensor that is able to fly and touch the bridge to take measurements during an inspection by contact. A practical application of the system involving the measurement of a bridge’s beam deflection using a laser tracking station is also presented. In order to validate our system, experiments on two different bridges involving the measurement of the deflection of their beams are shown.

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This paper presents a low weight (1.3 kg), human size dual arm system with compliant joints designed for aerial manipulation with a multirotor platform. Each arm provides four degrees of freedom (DOF) for end effector positioning in a kinematic configuration close to the human arm: shoulder pitch, roll and yaw, and elbow pitch. The aluminum frame structure of the arms has been designed with a double purpose: protecting the servo actuators against direct impacts and overloads, and allowing the integration of a compliant transmission mechanism with deflection measurement between the servo shaft and the output link. Mechanical joint compliance increases safety in the physical interactions with the environment, removing also joint overloads typical in closed kinematic chain configurations. The dual arm system has been integrated in a hexarotor platform with a visual servoing system for object grasping, evaluating its performance first in a fixed base test bench and later in outdoor flight tests.

The use of unmanned aerial systems for industrial applications has evolved considerably in recent years. This paper presents an aerial system capable of perching autonomously on pipes for inspection and maintenance in industrial environments. The target pipe to perch on is detected using a visual algorithm based on a semantic convolutional neuronal network. The information from a color camera is used to segment the image. Then, the segmentation information is fused with a depth image to estimate the pipe's pose, so that the pose of the robot can be controlled relative to it. The aerial robot is equipped with a soft landing system that robustly attaches it to the pipe. The article presents the complete development of the system. Experimental results performed in outdoor environments are shown.

This paper presents a crawling mechanism using a soft-tentacle gripper integrated into an unmanned aerial vehicle for pipe inspection in industrial environments. The objective was to allow the aerial robot to perch and crawl along the pipe, minimizing the energy consumption, and allowing to perform contact inspection. This paper introduces the design of the soft limbs of the gripper and also the internal mechanism that allows movement along pipes. Several tests have been carried out to ensure the grasping capability on the pipe and the performance and reliability of the developed system. This paper shows the complete development of the system using additive manufacturing techniques and includes the results of experiments performed in realistic environments.