The work in this thesis is concerned with the development of a novel and practical collision avoidance system for autonomous underwater vehicles (AUVs). Synergistically, advanced stochastic motion planning methods, dynamics quantisation approaches, multivariable tracking controller designs, sonar data processing and workspace representation, are combined to enhance significantly the survivability of modern AUVs. The recent proliferation of autonomous AUV deployments for various missions such as seafioor surveying, scientific data gathering and mine hunting has demanded a substantial increase in vehicle autonomy. One matching requirement of such missions is to allow all the AUV to navigate safely in a dynamic and unstructured environment. Therefore, it is vital that a robust and effective collision avoidance system should be forthcoming in order to preserve the structural integrity of the vehicle whilst simultaneously increasing its autonomy. This thesis not only provides a holistic framework but also an arsenal of computational techniques in the design of a collision avoidance system for AUVs. The design of an obstacle avoidance system is first addressed. The core paradigm is the application of the Rapidly-exploring Random Tree (RRT) algorithm and the newly developed version for use as a motion planning tool. Later, this technique is merged with the Manoeuvre Automaton (MA) representation to address the inherent disadvantages of the RRT. A novel multi-node version which can also address time varying final state is suggested. Clearly, the reference trajectory generated by the aforementioned embedded planner must be tracked. Hence, the feasibility of employing the linear quadratic regulator (LQG) and the nonlinear kinematic based state-dependent Ricatti equation (SDRE) controller as trajectory trackers are explored. The obstacle detection module, which comprises of sonar processing and workspace representation submodules, is developed and tested on actual sonar data acquired in a sea-trial via a prototype forward looking sonar (AT500). The sonar processing techniques applied are fundamentally derived from the image processing perspective. Likewise, a novel occupancy grid using nonlinear function is proposed for the workspace representation of the AUV. Results are presented that demonstrate the ability of an AUV to navigate a complex environment. To the author's knowledge, it is the first time the above newly developed methodologies have been applied to an A UV collision avoidance system, and, therefore, it is considered that the work constitutes a contribution of knowledge in this area of work.

A collision avoidance system for autonomous underwater vehicles

An underlying requirement for any Autonomous Underwater Vehicle (AUV) is to navigate through unknown or partly unknown environments while performing certain user specified tasks The loss of an AUV due to collision is unjustifiable both in terms of cost and replacement time To prevent such an unfortunate event, one requires a robust and effective Collision Avoidance System (CAS) This paper discusses the collision avoidance problem for the HUGIN AUVs In the first part, a complete simulator for the HUGIN AUV is implemented in matlab and simulink This includes a 6 degrees-of-freedom nonlinear AUV model, simulated environment including bottom profile and surface ice, navigation- and guidance functionality and sensor simulators In the second part a number of well known strategies for the collision avoidance problem is presented with a short analysis of their properties On the basis of the implemented simulator, a proposed CAS is developed and it’s performance is analyzed This system is based on simple principles and known collision avoidance strategies, in order to provide effective and robust performance The proposed system provides feasible solutions during all simulations and the collision avoidance maneuvers are performed in accordance with the specified user demands The developed simulator and collision avoidance system is expected to provide a suitable framework for further development and possibly a physical implementation on the HUGIN AUVs

3D AUV Collision Avoidance

The development of underwater robotic vehicles throughout the past 30 years has contributed significantly to various types of underwater search, survey, and recovery applications. To learn about these complex systems, the MIT Design of Ocean Systems Class of 1997 designed and built an inexpensive Autonomous Underwater Vehicle (AUV), Autolycus. The Design Class of 1998 further developed this vehicle, adding a sonar altimeter to its sensor array, as well as integrating a dead reckoning navigation system. In the spring of 1999, the design class was challenged to modify the AUV Autolycus to incorporate environment-based control and to double the vehicle's maximum controllable velocity. To succeed in these modifications, a thorough understanding of state-of-the-art AUV systems, design of new hardware and software systems, and extensive testing and evaluation of these systems were required. Results of these efforts included the addition of a five-channel sonar system, new main thrusters, and a new control algorithm used to control the new hardware. Preliminary successes in wall-following and other environment-triggered behaviors were achieved.

Katherine Croff

Papers

Development of an environment-sensitive navigation system for the AUV Autolycus