Collaborative autonomy in heterogeneous multi-robot systems

As autonomous mobile robots become increasingly connected and widely deployed in different domains, managing multiple robots and their interaction is key to the future of ubiquitous autonomous systems. Indeed, robots are not individual entities anymore. Instead, many robots today are deployed as part of larger fleets or in teams. The benefits of multirobot collaboration, specially in heterogeneous groups, are multiple. Significantly higher degrees of situational awareness and understanding of their environment can be achieved when robots with different operational capabilities are deployed together. Examples of this include the Perseverance rover and the Ingenuity helicopter that NASA has deployed in Mars, or the highly heterogeneous robot teams that explored caves and other complex environments during the last DARPA Sub-T competition. This thesis delves into the wide topic of collaborative autonomy in multi-robot systems, encompassing some of the key elements required for achieving robust collaboration: solving collaborative decision-making problems; securing their operation, management and interaction; providing means for autonomous coordination in space and accurate global or relative state estimation; and achieving collaborative situational awareness through distributed perception and cooperative planning. The thesis covers novel formation control algorithms, and new ways to achieve accurate absolute or relative localization within multi-robot systems. It also explores the potential of distributed ledger technologies as an underlying framework to achieve collaborative decision-making in distributed robotic systems. Throughout the thesis, I introduce novel approaches to utilizing cryptographic elements and blockchain technology for securing the operation of autonomous robots, showing that sensor data and mission instructions can be validated in an end-to-end manner. I then shift the focus to localization and coordination, studying ultra-wideband (UWB) radios and their potential. I show how UWB-based ranging and localization can enable aerial robots to operate in GNSS-denied environments, with a study of the constraints and limitations. I also study the potential of UWB-based relative localization between aerial and ground robots for more accurate positioning in areas where GNSS signals degrade. In terms of coordination, I introduce two new algorithms for formation control that require zero to minimal communication, if enough degree of awareness of neighbor robots is available. These algorithms are validated in simulation and real-world experiments. The thesis concludes with the integration of a new approach to cooperative path planning algorithms and UWB-based relative localization for dense scene reconstruction using lidar and vision sensors in ground and aerial robots

Developmentally deep perceptual system for a humanoid robot

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.Includes bibliographical references (p. 139-152).This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.This thesis presents a perceptual system for a humanoid robot that integrates abilities such as object localization and recognition with the deeper developmental machinery required to forge those competences out of raw physical experiences. It shows that a robotic platform can build up and maintain a system for object localization, segmentation, and recognition, starting from very little. What the robot starts with is a direct solution to achieving figure/ground separation: it simply 'pokes around' in a region of visual ambiguity and watches what happens. If the arm passes through an area, that area is recognized as free space. If the arm collides with an object, causing it to move, the robot can use that motion to segment the object from the background. Once the robot can acquire reliable segmented views of objects, it learns from them, and from then on recognizes and segments those objects without further contact. Both low-level and high-level visual features can also be learned in this way, and examples are presented for both: orientation detection and affordance recognition, respectively. The motivation for this work is simple. Training on large corpora of annotated real-world data has proven crucial for creating robust solutions to perceptual problems such as speech recognition and face detection. But the powerful tools used during training of such systems are typically stripped away at deployment. Ideally they should remain, particularly for unstable tasks such as object detection, where the set of objects needed in a task tomorrow might be different from the set of objects needed today. The key limiting factor is access to training data, but as this thesis shows, that need not be a problem on a robotic platform that can actively probe its environment, and carry out experiments to resolve ambiguity.(cont.) This work is an instance of a general approach to learning a new perceptual judgment: find special situations in which the perceptual judgment is easy and study these situations to find correlated features that can be observed more generally.by Paul Michael Fitzpatrick.Ph.D

From First Contact to Close Encounters: A Developmentally Deep Perceptual System for a Humanoid Robot

This thesis presents a perceptual system for a humanoid robot that integrates abilities such as object localization and recognition with the deeper developmental machinery required to forge those competences out of raw physical experiences. It shows that a robotic platform can build up and maintain a system for object localization, segmentation, and recognition, starting from very little. What the robot starts with is a direct solution to achieving figure/ground separation: it simply 'pokes around' in a region of visual ambiguity and watches what happens. If the arm passes through an area, that area is recognized as free space. If the arm collides with an object, causing it to move, the robot can use that motion to segment the object from the background. Once the robot can acquire reliable segmented views of objects, it learns from them, and from then on recognizes and segments those objects without further contact. Both low-level and high-level visual features can also be learned in this way, and examples are presented for both: orientation detection and affordance recognition, respectively. The motivation for this work is simple. Training on large corpora of annotated real-world data has proven crucial for creating robust solutions to perceptual problems such as speech recognition and face detection. But the powerful tools used during training of such systems are typically stripped away at deployment. Ideally they should remain, particularly for unstable tasks such as object detection, where the set of objects needed in a task tomorrow might be different from the set of objects needed today. The key limiting factor is access to training data, but as this thesis shows, that need not be a problem on a robotic platform that can actively probe its environment, and carry out experiments to resolve ambiguity. This work is an instance of a general approach to learning a new perceptual judgment: find special situations in which the perceptual judgment is easy and study these situations to find correlated features that can be observed more generally

A distributed simulation environment for multibody physics

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 1998.Includes bibliographical references (leaves 128-134).A distributed simulation environment, which can be used to model multibody physics, is developed. The software design is based on the object oriented paradigm and is implemented in C++ to run on a single workstation or multiple processors in parallel. It provides facilities to set up a multibody physics simulation, including arbitrary 3D geometric representation, particle interactions such as contacts and constraints, and visualization for postprocessing. Contact detection, the process of automatic identifying the geometric overlap between objects, is generally the most time-consuming procedure in the overall discrete element analysis pipeline. The computational cost of contact detection grows as a function of both the number of particles and the complexity of the geometric representation of each body. This thesis presents algorithms that significantly reduce the computational cost of the contact detection problem. The hashtable-based spatial reasoning algorithm demonstrates an O(M) performance, where M is the number of particles in the simulation system for a restricted set of particles. The discrete function representation (DFR) scheme is employed to model the surface geometry of complex 3D objects. DFR-based contact detection between a pair of objects exhibits an O(N) running time performance, where N is the number of surface point used to represent each object. In practice this results in a significant speedup over traditional techniques. A distributed DEM simulation environment is built on top of a set of software tools which exploit the parallelism embedded in the DEM analysis and which take advantage of a high-speed communications network to achieve good parallel performance. The goal is of reducing the entire computing time of of large-scale simulation problems to order O(N) is shown to be achieveable using the algorithms described.by Jen-Diann Chiou.Ph.D

Long distance free-space quantum key distribution

In the age of information and globalisation, secure communication as well as the protection of sensitive data against unauthorised access are of utmost importance. Quantum cryptography currently provides the only way to exchange a cryptographic key between two parties in an unconditionally secure fashion. Owing to losses and noise of today's optical fibre and detector technology, at present quantum cryptography is limited to distances below a few 100 km. In principle, larger distances could be subdivided into shorter segments, but the required quantum repeaters are still beyond current technology. An alternative approach for bridging larger distances is a satellite-based system, that would enable secret key exchange between two arbitrary points on the globe using free-space optical communication. The aim of the presented experiment was to investigate the feasibility of satellite-based global quantum key distribution. In this context, a free-space quantum key distribution experiment over a real distance of 144 km was performed. The transmitter and the receiver were situated in 2500 m altitude on the Canary Islands of La Palma and Tenerife, respectively. The small and compact transmitter unit generated attenuated laser pulses, that were sent to the receiver via a 15-cm optical telescope. The receiver unit for polarisation analysis and detection of the sent pulses was integrated into an existing mirror telescope designed for classical optical satellite communications. To ensure the required stability and efficiency of the optical link in the presence of atmospheric turbulence, the two telescopes were equipped with a bi-directional automatic tracking system. Still, due to stray light and high optical attenuation, secure key exchange would not be possible using attenuated pulses in connection with the standard BB84 protocol. The photon number statistics of attenuated pulses follows a Poissonian distribution. Hence, by removing a photon from all pulses containing two or more photons, an eavesdropper could measure its polarisation without disturbing the polarisation state of the remaining pulse. In this way, he can gain information about the key without introducing detectable errors. To protect against such attacks, the presented experiment employed the recently developed method of using additional "decoy" states, i.e., the the intensity of the pulses created by the transmitter were varied in a random manner. By analysing the detection probabilities of the different pulses individually, a photon-number-splitting attack can be detected. Thanks to the decoy-state analysis, the secrecy of the resulting quantum key could be ensured despite the Poissonian nature of the emitted pulses. For a channel attenuation as high as 35 dB, a secret key rate of up to 250 bit/s was achieved. Our outdoor experiment was carried out under real atmospheric conditions and with a channel attenuation comparable to an optical link from ground to a satellite in low earth orbit. Hence, it definitely shows the feasibility of satellite-based quantum key distribution using a technologically comparatively simple system

Investigation of Multimodal Template-Free Biometric Techniques and Associated Exception Handling

The Biometric systems are commonly used as a fundamental tool by both government and private sector organizations to allow restricted access to sensitive areas, to identify the criminals by the police and to authenticate the identification of individuals requesting to access to certain personal and confidential services. The applications of these identification tools have created issues of security and privacy relating to personal, commercial and government identities. Over the last decade, reports of increasing insecurity to the personal data of users in the public and commercial domain applications has prompted the development of more robust and sound measures to protect the personal data of users from being stolen and spoofing. The present study aimed to introduce the scheme for integrating direct and indirect biometric key generation schemes with the application of Shamir‘s secret sharing algorithm in order to address the two disadvantages: revocability of the biometric key and the exception handling of biometric modality. This study used two different approaches for key generation using Shamir‘s secret sharing scheme: template based approach for indirect key generation and template-free. The findings of this study demonstrated that the encryption key generated by the proposed system was not required to be stored in the database which prevented the attack on the privacy of the data of the individuals from the hackers. Interestingly, the proposed system was also able to generate multiple encryption keys with varying lengths. Furthermore, the results of this study also offered the flexibility of providing the multiple keys for different applications for each user. The results from this study, consequently, showed the considerable potential and prospect of the proposed scheme to generate encryption keys directly and indirectly from the biometric samples, which could enhance its success in biometric security field