Design of obstacle detection and avoidance system for GUANAY II AUV

Postprint (published version

Design of the obstacle detection system with the SONAR MK3 on Guanay II AUV

Autonomous underwater vehicles (AUV) perform inspection missions and intervention in known and unknown environments, where it is necessary to ensure their safety. The AUV must have the ability to detect and avoid obstacles in the path of navigation. This article, an obstacle detection system for experimental Guanay II AUV is proposed, using a mechanical scanning SONAR Tritech Micron MK3. Since Guanay II operates autonomously, we have designed software that allows adjustment and control of the parameters of SONAR, and the acquisition and processing of the signals obtained. Experimental tests at sea have allowed to verify the correct operation of software designed, as well as, experimental tests in a controlled environment have allowed to determine the optimal values of the basic parameters of SONAR.Postprint (published version

Assessment of Collision Avoidance Strategies for an Underwater Transportation System

Transportation using multiple autonomous vehicles with detection avoidance capability is useful for military applications. It is important for such systems to avoid collisions with underwater obstacles in an effective way, while keeping track of the target location. In this paper, sensor-based and path-planning methods of external collision avoidance were investigated for an underwater transportation system. In particular, sensor-based wall-following and hard-switching collision avoidance strategies and an offline RRT* path-planning method was implemented on the simulation model of the transportation system of four Hovering Autonomous Underwater Vehicles (HAUVs). Time-domain motion simulations were performed with each method and their ability to avoid obstacles was compared. The hard-switching method resulted in high yaw moments which caused the vehicle to travel towards the goal by a longer distance. Conversely, in the wall-following method, the yaw moment was kept to zero. Moreover, the wall-following method was found to be better than the hard-switching method in terms of time and power efficiency. The comparison between the offline RRT* path-planning and wall-following methods showed that the fuel efficiency of the former is higher whilst its time efficiency is poorer. The major drawback of RRT* is that it can only avoid the previously known obstacles. In future, offline RRT* and wall following can be blended for a better solution. The outcome of this paper provides guidance for the selection of the most appropriate method for collision avoidance for an underwater transportation system

Virtual reality based multi-modal teleoperation using mixed autonomy

The thesis presents a multi modal teleoperation interface featuring an integrated virtual reality based simulation aumented by sensors and image processing capabilities onboard the remotely operated vehicle. The virtual reality interface fuses an existing VR model with live video feed and prediction states, thereby creating a multi modal control interface. Virtual reality addresses the typical limitations of video-based teleoperation caused by signal lag and limited field of view thereby allowing the operator to navigate in a continuous fashion. The vehicle incorporates an on-board computer and a stereo vision system to facilitate obstacle detection. A vehicle adaptation system with a priori risk maps and real state tracking system enables temporary autonomous operation of the vehicle for local navigation around obstacles and automatic re-establishment of the vehicle\u27s teleoperated state. As both the vehicle and the operator share absolute autonomy in stages, the operation is referred to as mixed autonomous. Finally, the system provides real time update of the virtual environment based on anomalies encountered by the vehicle. The system effectively balances the autonomy between the human operator and on board vehicle intelligence. The reliability results of individual components along with overall system implementation and the results of the user study helps show that the VR based multi modal teleoperation interface is more adaptable and intuitive when compared to other interfaces

Fault-tolerant formation driving mechanism designed for heterogeneous MAVs-UGVs groups

A fault-tolerant method for stabilization and navigation of 3D heterogeneous formations is proposed in this paper. The presented Model Predictive Control (MPC) based approach enables to deploy compact formations of closely cooperating autonomous aerial and ground robots in surveillance scenarios without the necessity of a precise external localization. Instead, the proposed method relies on a top-view visual relative localization provided by the micro aerial vehicles flying above the ground robots and on a simple yet stable visual based navigation using images from an onboard monocular camera. The MPC based schema together with a fault detection and recovery mechanism provide a robust solution applicable in complex environments with static and dynamic obstacles. The core of the proposed leader-follower based formation driving method consists in a representation of the entire 3D formation as a convex hull projected along a desired path that has to be followed by the group. Such an approach provides non-collision solution and respects requirements of the direct visibility between the team members. The uninterrupted visibility is crucial for the employed top-view localization and therefore for the stabilization of the group. The proposed formation driving method and the fault recovery mechanisms are verified by simulations and hardware experiments presented in the paper