Oceans cover 71% of the earth's surface and contribute the largest reservoir of life on the earth. With more and more concern about the abounding and valuable ocean resources, these years have witnessed a remarkable growth in the wide range of underwater commercial activities for ocean survey, especially focusing on undersea exploration and exploitation, and even extensively for salvage operations related with disastrous accidents occurred undersea (Lapierre, 2006).
There are three main kinds of vehicles recruited for underwater activities. Manned Submersibles and Manned Underwater Vehicles with good abilities of directly manoeuvring and in-situ observation, have been widely utilized in commercial activity and scientific research, and reached the zenith in the late 1960s and early 1970s. However, this critical systems with vital importance of crew aboard and complex handling system significantly cost so much. Then, Remotely Operated Vehicles (ROVs) still with human in the loop but not in the vehicle are successful substitutes, being low-cost vehicles piloting in deep water greater than 1000ft. Today, ROV becomes a well-established technology frequently used in the offshore industry, most notably in the commercial offshore oil and gas, nuclear, pipeline and cable industries. Nevertheless, the long umbilical cable, linked with the mother ship, greatly inhibits the speed of the ROV, requiring the mother ship equipped with deck gear capable of winding up this cable and significantly restricting ship movement while deployed. More recently, with the development of advanced underwater technology, Autonomous Underwater Vehicles (AUVs) are steadily becoming the next significative step in ocean exploration due to their freedom from the constraints of an umbilical cable. Nowadays there has been gradually growth in the AUV industry worldwide which would be on an unprecedented scale and AUVs will carry out interventions in undersea structures in the future (Whitcomb, 2000). Moreover, recent applications using Intervention Autonomous Underwater Vehicles (IAUVs), have demonstrated the feasibility of autonomous underwater manipulations (Xu et al., 2007), controlled via acoustic links, thus removing the parasite effects of the umbilical cable (http://www.freesubnet.eu). With further research results and technological advances, AUVs have the potential for supplementing or even substituting ROVs for deep water operations, and AUVs in a team hold considerable potential for challenging scientific and commercial mission at sea. As a group of coordinated multiple robots dealing with tasks provides flexibility, robustness and efficiency beyond what is possible with single robot, there is one attractive scenario for underwater activities--the AUV team concept, which could be a mix of several low-cost specific purpose AUVs, guided and controlled by one or two higher cost AUVs (Xiang et al., 2008). The employment of multiple AUVs has significant advantages for both military and commercial applications (Bourgeois et al., 1999). A team of underwater vehicles could survey large ocean areas more rapidly and economically than that could be accomplished with a single AUV or ship (McDowell et al., 2002). The key point to the operation of AUVs is the availability of accurate navigation and positioning systems, which provide the measurement of the angular and linear positions of each underwater vehicle in the team and is therefore crucial to control and stabilize the platform. Unfortunately, one of the major problems that prevents the commercial application of AUVs, or at least mitigate their efficiency, is just that of vehicle navigation. On board navigation systems, as inertial navigation systems (INS), can not maintain the requested accuracy over the long time vehicle manoeuvring and are highly expensive as well as the inconvenient calibration for different AUV systems due to its vehicle-specific characteristic (Caiti et al., 1999). There are several positioning and navigation systems currently employed by AUVs researchers. The traditional acoustic navigation methods will be reviewed in section 2, and the main non-acoustic approach, which is also a dominant approach for AUVs, is combining a GPS receiver and an INS in one AUV (INS/GPS). That is, the vehicle mainly depends on the INS to be navigated, but periodically comes to surface to receive the GPS signal and to recalibrate the INS (Yun et al., 1999).When one group of AUVs is traveling to the area of interest, inter-vessel communications could also be used to provide the information of position and navigation, and then the team of AUVs relies on machine learning techniques for creation and maintenance of loose formation. But there is an important assumption that still at least one vehicle has an accurate positioning system on board, typically with the INS combined with GPS. That means at least one of the AUVs must periodically come to the surface to calibrate the position which would severely disturb or even deteriorate the whole strategy of the team coordination and formation, besides the unwanted energy consumed to heave up to the surface and the high cost of INS.
Accounting for the disadvantage of currently positioning and navigation approach for coordinated AUVs team mentioned above, another promising scheme is the heterogenous autonomous vehicle team concept to overcome the navigation problem, which would be a mix of several low-cost specific purpose vehicles which typically are AUVs, guided and controlled by one or two higher cost control vessels which typically are ASVs. Benefited from the underwater GPS concept combining the DGPS technology, a dedicated novel cooperative underwater acoustic navigation approach is suitable for this heterogenous vehicle team. The central control ASV can get high precise positions of AUVs without INS/GPS on board, allocates the waypoints to the AUVs as well as provide the navigation information via acoustic modem and also move above the central of mass of the AUVs, so that the whole team with heterogenous vehicles could conveniently implement the coordinated search or rescue scenario as a whole (Xiang et al., 2007).
The rest of this chapter is organized as follows. In section 2 the traditional underwater acoustic navigation system and the underwater GPS concept are reviewed, and the hardware implementation of DGPS intelligent sonobuoys as well as the novel cooperative navigation architecture for heterogeneous autonomous vehicle is presented in section 3. Section 4 includes a detailed description of the cooperative navigation algorithm for coordinated underwater vehicles. Section 5 provides the simulation results of the acoustic navigation. Section 6 draws conclusions. Section 7 makes acknowledgement for the support from co-authors and related scientific research projects.
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