Alexander Bahr

Cooperative localization for autonomous underwater vehicles

This paper describes an algorithm for distributed acoustic navigation for Autonomous Underwater Vehicles (AUVs). Whereas typical AUV navigation systems utilize pre-calibrated arrays of static transponders, our work seeks to create a fully mobile network of AUVs that perform acoustic ranging and data exchange with one another to achieve cooperative positioning for extended duration missions over large areas. The algorithm enumerates possible solutions for the AUV trajectory based on dead-reckoning and range-only measurements provided by acoustic modems that are mounted on each vehicle, and chooses the trajectory via minimization of a cost function based on these constraints. The resulting algorithm is computationally efficient, meets the strict bandwidth requirements of available AUV modems, and has potential to scale well to networks of large numbers of vehicles. The method has undergone extensive experimentation, and results from three different scenarios are reported in this paper, each of which utilizes MIT SCOUT Autonomous Surface Craft (ASC) as convenient platforms for testing. In the first experiment, we utilize three ASCs, each equipped with a Woods Hole acoustic modem, as surrogates for AUVs. In this scenario, two ASCs serve as Communication/Navigation Aids (CNAs) for a third ASC that computes its position based exclusively on GPS positions of the CNAs and acoustic range measurements between platforms. In the second scenario, an undersea glider is used in conjunction with two ASCs serving as CNAs. Finally, in the third experiment, a Bluefin12 AUV serves as the target vehicle. All three experiments demonstrate the successful operation of the technique with real ocean data.

Experiments in moving baseline navigation using autonomous surface craft

This paper describes an on-going research effort to achieve real-time cooperative localization of multiple autonomous underwater vehicles. We describe a series of experiments that utilize autonomous surface craft (ASC), equiped with undersea acoustic modems, GPS, and 802.11b wireless Ethernet communications, to acquire data and develop software for cooperative localization of distributed vehicle networks. Our experiments demonstrate the capability of the Woods Hole acoustic modems to provide accurate round-trip and one-way range measurements, as well as data transfer, for a fully mobile network of vehicles in formation flight. Finally, we present preliminary results from initial experiments involving cooperative operation of an Odyssey III AUV and two ASCs, demonstrating ranging and data transfer from the ASCs to the Odyssey III.

Acoustic behaviour of echolocating porpoises during prey capture

SUMMARY Porpoise echolocation has been studied previously, mainly in target detection experiments using stationed animals and steel sphere targets, but little is known about the acoustic behaviour of free-swimming porpoises echolocating for prey. Here, we used small onboard sound and orientation recording tags to study the echolocation behaviour of free-swimming trained porpoises as they caught dead, freely drifting fish. We analysed porpoise echolocation behaviour leading up to and following prey capture events, including variability in echolocation in response to vision restriction, prey species, and individual porpoise tested. The porpoises produced echolocation clicks as they searched for the fish, followed by fast-repetition-rate clicks (echolocation buzzes) when acquiring prey. During buzzes, which usually began when porpoises were about 1–2 body lengths from prey, tag-recorded click levels decreased by about 10 dB, click rates increased to over 300 clicks per second, and variability in body orientation (roll) increased. Buzzes generally continued beyond the first contact with the fish, and often extended until or after the end of prey handling. This unexplained continuation of buzzes after prey capture raises questions about the function of buzzes, suggesting that in addition to providing detailed information on target location during the capture, they may serve additional purposes such as the relocation of potentially escaping prey. We conclude that porpoises display the same overall acoustic prey capture behaviour seen in larger toothed whales in the wild, albeit at a faster pace, clicking slowly during search and approach phases and buzzing during prey capture.

Autonomous Underwater Vehicle Navigation

This chapter surveys the problem of navigation for autonomous underwater vehicles (AUV s). Navigation is critical for the safety and effectiveness of AUV missions. The unavailability of global positioning system (GPS ) underwater makes AUV navigation a challenging research problem. Recent years have seen considerable improvements in performance and reduction in the cost and size of the various sensor devices available for ocean vehicle navigation. In concert with these developments, advances in algorithms such as simultaneous localization and mapping, and cooperative navigation have enabled dramatic improvements in the navigation capabilities of AUVs. These improvements in AUV navigation have contributed to the successful deployment of AUVs for a wide variety of applications over the past decade.

Indoor navigation research with the Khepera III mobile robot: An experimental baseline with a case-study on ultra-wideband positioning

Recent substantial progress in the domain of indoor positioning systems and a growing number of indoor location-based applications are creating the need for systematic, efficient, and precise experimental methods able to assess the localization and perhaps also navigation performance of a given device. With hundreds of Khepera III robots in academic use today, this platform has an important potential for single- and multi-robot localization and navigation research. In this work, we develop a necessary set of models for mobile robot navigation with the Khepera III platform, and quantify the robots localization performance based on extensive experimental studies. Finally, we validate our experimental approach to localization research by considering the evaluation of an ultra-wideband (UWB) positioning system. We successfully show how the robotic platform can provide precise performance analyses, ultimately proposing a powerful approach towards advancements in indoor positioning technology.

Low-cost collaborative localization for large-scale multi-robot systems

Large numbers of collaborating robots are advantageous for solving distributed problems. In order to efficiently solve the task at hand, the robots often need accurate localization. In this work, we address the localization problem by developing a solution that has low computational and sensing requirements, and that is easily deployed on large robot teams composed of cheap robots. We build upon a real-time, particle-filter based localization algorithm that is completely decentralized and scalable, and accommodates realistic robot assumptions including noisy sensors, and asynchronous and lossy communication. In order to further reduce this algorithms overall complexity, we propose a low-cost particle clustering method, which is particularly well suited to the collaborative localization problem. Our approach is experimentally validated on a team of ten real robots.

Toward the Deployment of an Ultra-Wideband Localization Test Bed

The design, development, and deployment of Ultra-Wideband (UWB) localization systems involves digital and Radio-Frequency (RF) hardware, embedded software, localization algorithms, security and reliability aspects, electromagnetics, and others. Design and integration decisions affect the performance of an UWB system, in particular the most important metrics: localization accuracy and position update rate. To facilitate further development of UWB localization systems and to analyze some of the major trade-offs we share our experience in deploying the EPFL UWB-Lite test bed (U-Lite). We describe an approach to numerical simulation modeling that can help in the design and evaluation of UWB localization systems. To validate our approach we show experimental results with one transmitter and one receiver. Our UWB test bed includes a mobile robot platform, so we can study and evaluate the UWB performance trade-offs in real-world conditions.

Modeling and benchmarking Ultra-Wideband localization for mobile robots

Ultra-Wideband Impulse Radio (UWB-IR) is a technology that has great potential to solve numerous mobile robotic and asset tracking problems in GPS-denied environments. Our goal is to help software and hardware designers in improving the state-of-the-art in UWB-based robotic localization. We developed a test-bed where an UWB transmitter is attached to a mobile robot. By combining the received signals with the robots position log acquired through the dead-reckoning sensors, we obtain UWB signals which are well referenced with respect to the transmitter-receiver distance and orientation. In addition, we provide a model for every component of the setup. The entire setup allows us to simulate from first principles every aspect of an UWB localization system and then to implement low-level signal processing as well as higher-level modulation and localization techniques. We implement an Automatic Gain Control (AGC) algorithm to demonstrate the rapid proto-typing capabilities of the test-bed. Our work shows how an UWB robotic system and its models can be involved in all phases of the development of a technology that can help robots navigation, localization and communication algorithms.

Distributed Spatiotemporal Suppression for Environmental Data Collection in Real-World Sensor Networks

Environmental processes are often severely oversampled. As sensor networks become more ubiquitous for this purpose, increasing network longevity becomes ever more important. Radio transceivers in particular are a great source of energy consumption, and many networking algorithms have been proposed that seek to minimize their use. Traditionally, such approaches are often data agnostic, i.e., their performance is not dependent on the properties of the data they transport. In this paper we explore algorithms that exploit environmental relationships in order to reduce the amount of transmitted data while maintaining expected levels of accuracy. We employ a realistic testing environment for evaluating the power savings brought by such algorithms, based on Sensorscope, a commercial sensor network product for environmental monitoring. We implement and test a suppression-based data collection algorithm from literature that to our knowledge has never been implemented on a real system, and propose modifications that make it more suitable for real-world conditions. Using a custom extension board developed for in situ power monitoring, we show that while the algorithms greatly reduce the amount of energy spent on transmitting packets, they have no effect on the real systems overall power consumption due to its preexisting network architecture.

Evaluating Efficient Data Collection Algorithms for Environmental Sensor Networks

Although there exists a large body of work on efficient data collection in sensor networks, the vast majority of proposed techniques have not been implemented on real networks or thoroughly studied on real data. As algorithm performance is highly dependent on the characteristics of the data being reported, it is very difficult to make suggestions as to the relative performance of any particular method. In this work we seek to compare and evaluate existing approaches to efficient data gathering in the specific context of environmental monitoring.We examine a choice algorithm that has not, to the best of our knowledge, been thoroughly studied on real data. We detail a number of algorithmic modifications necessary to bring it from theory to reality, and study the algorithm’s performance in simulation using extensive traces from real world sensor network deployments.