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This paper presents a modularized autonomous pipeline inspection robot called MRINSPECT VII+, which we recently developed. MRINSPECT VII+ is aimed at inspect in-service urban gas pipelines with a diameter of 200 mm. The robot consists of five basic modules: driving, sensing, joint, and battery modules. For nondestructive testing (NDT), an NDT module can be added to the system. The driving module uses a multiaxial differential gear mechanism to provide traction forces to the robot. The sensor module recognizes the pipeline element using position-sensitive detector (PSD) sensors and a CCD camera. The control module contains a computing unit and manages the robot’s autonomous navigation. The battery module supplies power to the system. Each module is connected via backdrivable active joint modules, which provide flexibility while moving inside narrow pipelines. Additionally, the wireless communication module helps the system communicate with the ground station. We tested MRINSPECT VII+ in real pipeline environments and validated its feasibility successfully.

In this study, the end-effector tracking performance of a manipulator installed on a remotely operated vehicle (ROV) for autonomous underwater intervention is verified. The underwater manipulator is an ARM 7E MINI model produced by the ECA group, which consists of six joints and one gripper. Of the six joints of the manipulator, two are revolute joints and the other four are prismatic joints. Velocity control is used to control the manipulator with forward and inverse kinematics. When the manipulator approaches a target object, it is difficult for the ROV to maintain its position and posture, owing to various disturbances, such as the variation in both the center of mass and the reaction force resulting from the manipulator motion. Therefore, it is necessary to compensate for the influences and ensure the relative distance to the object. Simulations and experiments are performed to track the trajectory of a virtual object, and the tracking performance is verified from the results.

The use of autonomous marine robots has been rapidly increasing in the development of marine environments. This paper presents the development of an autonomous surface vehicle (ASV) and validation of autonomous navigation technologies. The ASV was developed as a testbed to validate fundamental navigation technologies for autonomous marine robots including both surface and underwater vehicles. The ASV was developed on a catamaran by integrating various sensors and power and electrical propulsion systems, navigation and control systems, and communication devices. As fundamental navigation technologies for ASV, waypoint tracking and obstacle avoidance are developed and tested. Further, using the ASV as a testbed to validate underwater navigation technologies, two types of underwater localization methods were developed. First, an acoustic-based navigation was developed by using acoustic sources as landmarks in underwater environment. The proposed acoustic-based navigation localized both vehicle and source by Kalman filter-based SLAM. Second, terrain-based localization as geophysics-based navigation was developed using a particle filter. Effective resampling can be achieved by using a measurement of terrain roughness. Both acoustic and terrain-based underwater navigation methods are implemented with the developed ASV, and the performance of the navigation methods are evaluated by comparing the estimated localization results to the ground truth acquired by GPS. Several field tests conducted in inland water environments demonstrate the performance of the developed vehicle and navigation algorithms.

KRISO (Korea Research Institute of Ship & Ocean Engineering) started a project to develop the core algorithms for autonomous intervention using an underwater robot in 2017. This paper introduces the development of the robot platform for the core algorithms, which is an ROV (Remotely Operated Vehicle) type with one 7-function manipulator. Before the detailed design of the robot platform, the 7E-MINI arm of the ECA Group was selected as the manipulator. It is an electrical type, with a weight of 51 kg in air (30 kg in water) and a full reach of 1.4 m. To design a platform with a small size and light weight to fit in a water tank, the medium-size manipulator was placed on the center of platform, and the structural analysis of the body frame was conducted by ABAQUS. The robot had an IMU (Inertial Measurement Unit), a DVL (Doppler Velocity Log), and a depth sensor for measuring the underwater position and attitude. To control the robot motion, eight thrusters were installed, four for vertical and the rest for horizontal motion. The operation system was composed of an on-board control station and operation S/W. The former included devices such as a 300 VDC power supplier, Fiber-Optic (F/O) to Ethernet communication converter, and main control PC. The latter was developed using an ROS (Robot Operation System) based on Linux. The basic performance of the manufactured robot platform was verified through a water tank test, where the robot was manually operated using a joystick, and the robot motion and attitude variation that resulted from the manipulator movement were closely observed.

This paper presents development of an autonomous surface vehicle (ASV) and validation of its performance. The ASV was developed on a catamaran by integrating various sensors and systems, including power and electrical propulsion, navigation and control, and communication devices. The vehicle has two main purposes; 1) Development of autonomous navigation technology for surface vehicle, and 2) Validation of underwater navigation technology before applying to autonomous underwater vehicle (AUV). The vehicle is used as testbed to evaluate the navigation technologies for both surface and underwater environment. So, it is developed to be equipped with various kinds of navigation sensors. For surface navigation, basic performance of the vehicle, way point tracking and obstacle avoidance are evaluated. For underwater navigation, acoustic based SLAM and terrain based localization are developed and demonstrated using the developed vehicle. Several times of field test conducted in inland water environment demonstrate the performance of the developed vehicle and navigation algorithms.

This paper proposes a vision-based underwater laser scanner with separate structures for an underwater camera and a line laser projector. Because the two devices can be adaptively placed regardless of the features of the unmanned underwater vehicle (UUV), the scanner has significant advantages in relation to its availability and flexibility. Position calibration between the underwater camera and laser projector guarantees a 3D measuring performance with high accuracy. To verify the proposed underwater laser scanner, a test-bed system was manufactured, which consisted of the laser projector, camera, Pan&Tilt, and Attitude and Heading Reference System (AHRS). A camera-laser calibration test and simple 3D reconstruction test were performed in a water tank and the experimental results are reported.

This paper addresses the field applications of an autonomous surface vehicle (ASV) for the development of underwater navigation and mapping systems. The ASV was developed on a catamaran by integrating various sensors and systems, including power and electrical propulsion, navigation and control, and communication devices. The authors are currently working on the development of acoustic-based navigation and geophysical mapping systems for autonomous underwater vehicles (AUVs) and an ASV is used for its preliminary validation. As ASVs can provide georeferenced (i.e., GPS) data, the performance of the developed navigation and mapping algorithms can be efficiently estimated. In the field test, the ASV performs two tasks: underwater acoustic-source searching and underwater geomagnetic-field-data gathering. Underwater acoustic data were used to validate the acoustic-based underwater navigation approach, and geomagnetic data were applied to build an underwater geophysical map. This paper presents the development process of the ASV and its practical application, along with the underwater navigation and mapping results.

This paper presents a camera-laser scanner system for underwater ranging and preliminary results of three-dimensional (3D) object recognition. Calibration between the camera and the laser is necessary to obtain precise 3D information. To accomplish this, we adopted a triangulation-based method proposed by Forest and Collado (New methods for triangulation-based shape acquisition using laser scanners. Univeritat de Girona, 2004 [1]) and designed a simple image processing sequence to detect a projected laser line on the image. Using precise ranging measurement from laser scanner, underwater 3D objects were reconstructed and recognized in virtual 3D space. To verify the performance of a laser scanner and the 3D recognition, we performed an experiment in a water tank.

This paper describes remotely operated vehicles and the preliminary experiment results for system identification. The robot used in this study is a remotely operated vehicle that is under development by Korea Research Institute of Ships and Ocean Engineering. It is controlled by eight thrusters and is equipped with an inertia measurement unit, Doppler velocity log, pressure sensor, light emitting diode lighting, and analog camera. This paper presents the results of the towing test and free floating experiment in a water tank for system identification of the remotely operated vehicle. The proposed system identification method determines the dynamic parameters of a vehicle to design a controller for precise control. The proposed method can obtain 2-degrees-of-freedom model parameters for the vehicle.

This paper describes the development of an autonomous surface vehicle (ASV) and navigation techniques for autonomously performing various tasks in marine environments with a minimization of human operator interference. The ASV platform mounts a variety of sensors and devices, and it is designed on a catamaran hull form to provide more stability in maneuvering motions. Intelligent autonomy capabilities including waypoint tracking and collision avoidance approaches are fundamentally implemented in an on-board system, for improving the autonomy levels of the ASV. Specifically, potential risk areas where a likelihood of collision between the maneuvering ASV and a static obstacle exists are configured on a predicted trajectory of the vehicle. Then, a collision-free path is generated by a Dubins curve approach considering the turning radius of the vehicle. To demonstrate the performance and feasibility of the developed ASV, preliminary field tests were carried out in inland water environments, and the results are discussed.