Paul Michael Newman Doctor of Philosophy The University of Sydney March 1999 On the Structure and Solution of the Simultaneous Localisation and Map Building Problem This thesis is concerned with the simultaneous localisation and map building (SLAM) problem. The SLAM problem asks if it is possible for an autonomous vehicle to start in an unknown location in an unknown environment and then to incrementally build a map of this environment while simultaneously using this map to compute absolute vehicle location. The map and robot location estimates obtained from a successful SLAM system provide essential information upon which high level tasks such as path planning are predicated. A practicable solution to the SLAM problem is of inestimable value in the quest to create a truly autonomous mobile robot. The thesis has three principal theoretical contributions. The first is the elucidation of the structure of the SLAM problem. This is achieved by the analysis of a conventional and well known SLAM algorithm using global coordinates called, in this thesis, the Absolute Map Filter or AMF. Using this algorithm, three convergence theorems central to the SLAM problem are proved for the first time. They prove that the uncertainty in the estimated map decreases monotonically and achieves a defined lower bound. Futhermore, in the limit as the number of landmark observations increases, the relationship between landmarks becomes perfectly known. These proofs constitute the second theoretical contribution of the thesis. The third principal theoretical contribution of this thesis is the development of a novel SLAM solution capable of solving the SLAM problem in real time. This algorithm is called the Geometric Projection Filter or GPF. Rather than estimate the location of landmarks in global coordinates it estimates the relationships between individual landmarks. The convergence properties of this algorithm are derived and compared with those of the conventional AMF algorithm. An implementation of the GPF and the AMF is provided on a custom built subsea vehicle. The performance of the two filters are compared and shown to have the properties predicted by the preceding theoretical analysis. This implementation constitutes the fourth principal contribution of the thesis. It shows that the GPF can be used as the basis of a substantive real time deployment of a mobile robot in an initially unknown environment.

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On the Structure and Solution of the Simultaneous Localisation and Map Building Problem

Surface ship and submarine magnetic field signatures have been exploited for over 80 years by naval influence mines, and both underwater and airborne surveillance systems. The generating mechanism of the four major shipboard sources of magnetic fields is explained, along with a detailed description of the induced and permanent ferromagnetic signature characteristics. A brief historical summary of magnetic naval mine development during World War II is followed by a discussion of important improvements found in modern weapons, including an explanation of the damage mechanism for non-contact explosions. A strategy for selecting an optimum mine actuation threshold is given. A multi-layered defensive strategy against naval mines is outlined, with graphical explanations of the relationships between ship signature reduction and minefield clearing effectiveness. In addition to a brief historical discussion of underwater and airborne submarine surveillance systems and magnetic field sensing principles, ma...

Exploitation of a ship's magnetic field signatures

This thesis develops an approach to the construction of multidimensional stochastic models for intelligent systems exploring an underwater environment. It describes methods for building models by a three- dimensional spatial decomposition of stochastic, multisensor feature vectors. New sensor information is incrementally incorporated into the model by stochastic backprojection. Error and ambiguity are explicitly accounted for by blurring a spatial projection of remote sensor data before incorporation. The stochastic models can be used to derive surface maps or other representations of the environment. The methods are demonstrated on data sets from multibeam bathymetric surveying, towed sidescan bathymetry, towed sidescan acoustic imagery, and high-resolution scanning sonar aboard a remotely operated vehicle.

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Multisensor Modeling Underwater with Uncertain Information

A detection procedure for a moving magnetic dipole target by using at least three scalar magnetometers is proposed in this letter The magnetometers are deployed on the ground or seafloor, while the target is traveling along a straight line at a constant speed above the ground First, the range from each magnetometer to the closest point of approach (CPA) on the flight line as well as the instant that the target passes by the CPA is estimated by adopting the orthonormal basis function expansion method Then, the moving parameters, including the moving direction, speed, and elevation, are found through basic geometry relations Finally, the magnetic moment is determined by solving a linear system by using the least-squares method Both simulated and field experimental data are employed to demonstrate the proposed scheme

Detection of a Moving Magnetic Dipole Target Using Multiple Scalar Magnetometers

Sonars will continue to play an important role in world-modeling for autonomous underwater systems because of the greater range available to acoustic sensors compared with other sensing modalities. However, attempts to automate the interpretation of sidescan sonar data are typically based on two-dimensional image-processing and pattern-analysis techniques. Such sidescan "images" provide only indirect, qualitative, and view-dependent information, since the intensity of the returned signal is a function of both seafloor shape and scattering properties of the bottom materials. This overview of work in progress at the Deep Submergence Laboratory describes several techniques for three-dimensional sonar processing in which seafloor shape information is used to reduce geometric and radiometric dependencies in the intensity signal. The approach is developed using Sea Beam bathymetry and Sea MARC I sidescan data. Preliminary results are also described for new split beam sidescan sonars designed for high-resolution seafloor characterization. Complex-domain processing of the quadrature-sampled signal gives amplitude and phase for three-dimensional modeling, and offers a measure of signal coherence and modeling certainty. The processed output is a quantitative model of three-dimensional shape and backscatter characteristics that will be applied to feature classification and terrain-relative navigation for intelligent underwater vehicles.

Three-Dimensional Modeling of Seafloor Backscatter from Sidescan Sonar for Autonomous Classification and Navigation

Increasing interest in underwater autonomous vehicles has resulted in a search for suitable guidance systems. Magnetic techniques could provide supplementary guidance for autonomous vehicles that need occasional precise position fixes to update their standard navigational systems, or that want to return to a particular spot on the ocean bottom with great accuracy. A small permanent magnet resting at a precisely known spot on the ocean's bottom or naturally occurring key features in a magnetic survey of the bottom could provide the necessary magnetic signal. Of the several magnetic guidance approaches considered, an adaptive search technique seems the most promising. In adaptive search, the location of each successive search pass is determined by information gathered on the previous pass. Computer simulation results show that three search passes are usually sufficient to locate the center of the magnetic anomaly to within several feet. The favored sensor configuration is a scalar magnetometer whose outputs are successively subtracted along the path of sensor motion to form an approximation to the spatial gradient of the sensor's output. Data interpretation for this technique appears simple enough to be done automatically by either algorithmic or artificial intelligence techniques.

Magnetic Guidance of Autonomous Vehicles

A summary review is provided of underwater magnetic sensing with regard to present practice, new developments, and predicted future practice. Numerous applications of underwater magnetic sensing currently exist for research, commercial, and military interests. Thus, present applications range all the way from basic study of geologic faults, through exploration for offshore oil, to anti-submarine warfare. Important developments have occurred in recent years primarily with respect to more sensitive sensors, more sophisticated signal processing, improved modelling of target signatures, and a more intensive systems-oriented approach to design. These developments vail not only improve the performance of present applications but are expected to yield new applications in the near future such as target tracking, classification, and homing systems; navigation of robot vehicles by fixes on prerecorded geologic magnetic anomalies; and underwater communications by low frequency magnetic signals. The key to this dynamic future lies in reducing ambient magnetic noise to acceptable levels by signal processing and better systems design.

Current and Future Underwater Magnetic Sensing

Underwater acoustic transponder navigation requires knowing the effective source to transponder sound speed in order to convert ping return times to slant ranges for use in position fix calculations. This computer study determined that simple harmonic mean sound speed calculations can be used to compute the effective sound speed with acceptable accuracy for many ocean engineering applications. Thus, considerably more complex and time-consuming ray tracing calculations will usually not be required.

Harmonic Mean Sound Speed is Adequate for Transponder Navigation

An analysis is given of shallow water submarine detection by a buried magnetic loop. The submarine signal and interfering geomagnetic, ocean wave, and thermal noise are included in a simple, flexible detection range model. Sample detection ranges are presented and appear encouraging. Conditions which can limit detection are discussed. A simple experiment is planned as the logical next step. The detection model calculates detection ranges as a function of loop signal-to-noise ratio. The model allows for variation of loop, target, and ambient parameters as well as the detection criteria. Results illustrate that magnetic loops can be effective detectors. The loops are ambient noise limited. Random fluctuations about the earth's steady magnetic field; i.e., geomagnetic micropulsations, are the most serious noise source. Ocean wave induced noise creates a zone of intermediate depths where detection is impossible if the surface waves are large enough (such large, long-period waves are rarely encountered). Thermal noise arising from resistance in the loop's wire is very small. The thermal noise limit can be approached if the geomagnetic noise is highly correlated. A differential loop configuration (employing two loops) could then subtract out the geomagnetic noise yielding increased detection ranges.

D. Polvani

Papers

Magnetic Guidance of Autonomous Vehicles

Current and Future Underwater Magnetic Sensing

Harmonic Mean Sound Speed is Adequate for Transponder Navigation

Magnetic loops as submarine detectors