The active surveillance of public and private sites is increasingly becoming a very important and critical issue. It is therefore, imperative to develop mobile surveillance systems to protect these sites. Modern surveillance systems encompass spatially distributed mobile and static sensors in order to provide effective monitoring of persistent and transient objects and events in a given Area Of Interest (AOI). The realization of the potential of mobile surveillance requires the solution of different challenging problems such as task allocation, mobile sensor deployment, multisensor management, cooperative object detection and tracking, decentralized data fusion, and interoperability and accessibility of system nodes. This thesis proposes a market-based framework that can be used to handle different problems of mobile surveillance systems. Task allocation and cooperative target-tracking are studied using the proposed framework as two challenging problems of mobile surveillance systems. These challenges are addressed individually and collectively.

The active surveillance of public and private sites is increasingly becoming a very important and critical issue. It is therefore, imperative to develop mobile surveillance systems to protect these sites. Modern surveillance systems encompass spatially distributed mobile and static sensors in order to provide effective monitoring of persistent and transient objects and events in a given Area Of Interest (AOI). The realization of the potential of mobile surveillance requires the solution of different challenging problems such as task allocation, mobile sensor deployment, multisensor management, cooperative object detection and tracking, decentralized data fusion, and interoperability and accessibility of system nodes. This thesis proposes a market-based framework that can be used to handle different problems of mobile surveillance systems. Task allocation and cooperative target-tracking are studied using the proposed framework as two challenging problems of mobile surveillance systems. These challenges are addressed individually and collectively.

Active docking in modular robotic systems has received a lot of interest recently as it allows small versatile robotic systems to coalesce and achieve the structural benefits of larger robotic systems. This feature enables reconfigurable modular robotic systems to bridge the gap between small agile systems and larger robotic systems. The proposed self-reconfigurable mobile robot design exhibits dual mobility using a tracked drive for longitudinal locomotion and wheeled drive for lateral locomotion. The two degrees of freedom (DOF) docking interface referred to as GHEFT (Genderless, High strength, Efficient, Fail-Safe, high misalignment Tolerant) allows for an efficient docking while tolerating misalignments in 6-DOF. In addition, motion along the vertical axis is also achieved via an additional translational DOF, allowing for toggling between tracked and wheeled locomotion modes by lowering and raising the wheeled assembly. This thesis also presents a visual-based onboard Hybrid Target Tracking algorithm to detect and follow a target robot leading to autonomous docking between the modules. As a result of this proposed approach, the tracked features are then used to bring the robots in sufficient proximity for the docking procedure using Image Based Visual Servoing (IBVS) control. Experimental results to validate the robustness of the proposed tracking method, as well as the reliability of the autonomous docking procedure, are also presented in this thesis. / Master of Science / Active docking in modular robotic systems has received a lot of interest recently as it allows small versatile robotic systems to coalesce and achieve the structural benefits of larger robotic systems. This feature enables reconfigurable modular robotic systems to bridge the gap between small agile systems and larger robotic systems. Such robots can prove useful in environments that are either too dangerous or inaccessible to humans. Therefore, in this research, several specific hardware and software development aspects related to self-reconfigurable mobile robots are proposed. In terms of hardware development, a robotic module was designed that is symmetrically invertible and exhibits dual mobility using a tracked drive for longitudinal locomotion and wheeled drive for lateral locomotion. Such interchangeable mobility is important when the robot operates in a constrained workspace. The mobile robot also has integrated two degrees of freedom (DOF) docking mechanisms referred to as GHEFT (Genderless, High strength, Efficient, Fail-Safe, high misalignment Tolerant). The docking interface allows for an efficient docking while tolerating misalignments in 6-DOF. In addition, motion along the vertical axis is also performed via an additional translational DOF, allowing for lowering and raising the wheeled assembly. The robot is equipped with sensors to provide positional feedback of the joints relative to the target robot. In terms of software development, a visual-based onboard Hybrid Target Tracking algorithm for high-speed consistent tracking iv of colored targets is also presented in this work. The proposed technique is used to detect and follow a colored target attached to the target robot leading to autonomous docking between the modules using Image Based Visual Servoing (IBVS). Experimental results to validate the robustness of the proposed tracking approach, as well as the reliability of the autonomous docking procedure, are also presented in the thesis. The thesis is concluded with discussions about future research in both structured and unstructured terrains.

Submitted by Almir Azevedo (barbio1313@gmail.com) on 2015-08-24T17:42:07Z No. of bitstreams: 1 CARLOS ALEXANDRE F. JORGE D.pdf: 11356748 bytes, checksum: 59927b7a303fb41d249f403942824b9a (MD5) / Made available in DSpace on 2015-08-24T17:42:07Z (GMT). No. of bitstreams: 1 CARLOS ALEXANDRE F. JORGE D.pdf: 11356748 bytes, checksum: 59927b7a303fb41d249f403942824b9a (MD5) Previous issue date: 2015-07 / This work proposes the development of a system to evaluate received radiation dose for nuclear plants personnel. The system is conceived to operate in a complementary form to the existing approaches for radiological protection, thus o ering redundancy, what is desirable for critical plants operation. The proposed system must operate in an independent form on the actions to be performed by the operators under evaluation. Therefore, it was decided it would be based on methods used for video surveillance. The nuclear plant used as example is Argonauta Nuclear Research Reactor, belonging to Instituto de Engenharia Nuclear, Comiss~ao Nacional de Energia Nuclear (Nuclear Engineering Institute, National Nuclear Energy Commission). During this thesis research, both radiation dose rate distribution and video databases were obtained. Methods available in the literature, for targets detection and/or tracking, were evaluated for this database. From these results, a new system was proposed, with the purpose of meeting the requisites for this particular application. Given the tracked positions of each worker, the radiation dose received by each one during tasks execution is estimated, and may serve as part of a decision support system.

Approved for public release; distribution is unlimited / The thesis deals with the detection and tracking of dim point targets in infrared images. Research topics include image process modeling with adaptive two-dimensional Least Mean Square (LMS) and Recursive Least Squares (RLS) prediction filters. Target detection is performed by significance testing the prediction error residual. A pulse tracker is developed which may be adjusted to discriminate target dynamics. The methods are applicable to detection and tracking in other spectral bands. / http://archive.org/details/adaptivedimpoint00dema / Major, United States Marine Corps