Browsing by Subject "robotics"
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Item Cybernetic automata: An approach for the realization of economical cognition for multi-robot systems(2009-05-15) Mathai, Nebu JohnThe multi-agent robotics paradigm has attracted much attention due to the variety of pertinent applications that are well-served by the use of a multiplicity of agents (including space robotics, search and rescue, and mobile sensor networks). The use of this paradigm for most applications, however, demands economical, lightweight agent designs for reasons of longer operational life, lower economic cost, faster and easily-verified designs, etc. An important contributing factor to an agent?s cost is its control architecture. Due to the emergence of novel implementation technologies carrying the promise of economical implementation, we consider the development of a technology-independent specification for computational machinery. To that end, the use of cybernetics toolsets (control and dynamical systems theory) is appropriate, enabling a principled specifi- cation of robotic control architectures in mathematical terms that could be mapped directly to diverse implementation substrates. This dissertation, hence, addresses the problem of developing a technologyindependent specification for lightweight control architectures to enable robotic agents to serve in a multi-agent scheme. We present the principled design of static and dynamical regulators that elicit useful behaviors, and integrate these within an overall architecture for both single and multi-agent control. Since the use of control theory can be limited in unstructured environments, a major focus of the work is on the engineering of emergent behavior. The proposed scheme is highly decentralized, requiring only local sensing and no inter-agent communication. Beyond several simulation-based studies, we provide experimental results for a two-agent system, based on a custom implementation employing field-programmable gate arrays.Item Implementing Feedback Control on a Novel Proximity Operations Simulation Platform(2012-07-16) Aures-Cavalieri, Kurt DaleRecently, The Land, Air and Space Robotics (LASR) Laboratory has demonstrated a state-of-the-art proximity operations test bed that will revolutionize the concept of portable space systems simulation. The Holonomic Omni-directional Motion Emulation Robot (HOMER) permits in nite, un-tethered circumnavigations of one object by another. To allow this platform to operate at the desired performance, an appropriate implementation of feedback control is essential. The dynamic model is derived and presented using a Lagrangian approach. A Lyapunov method is used to form proportional-derivative (PD) and proportional-integral-derivative (PID) feedback controllers. These controllers are validated with computer-based simulation and compared through experimental results. Finally, a frequency analysis is performed in an effort to identify the bandwidth of the system and provide a better understanding of the expected system performance for reference motions containing harmonic perturbations.Item Intelligent Motion Planning and Analysis with Probabilistic Roadmap Methods for the Study of Complex and High-Dimensional Motions(2011-02-22) Tapia, LydiaAt first glance, robots and proteins have little in common. Robots are commonly thought of as tools that perform tasks such as vacuuming the floor, while proteins play essential roles in many biochemical processes. However, the functionality of both robots and proteins is highly dependent on their motions. In order to study motions in these two divergent domains, the same underlying algorithmic framework can be applied. This method is derived from probabilistic roadmap methods (PRMs) originally developed for robotic motion planning. It builds a graph, or roadmap, where configurations are represented as vertices and transitions between configurations are edges. The contribution of this work is a set of intelligent methods applied to PRMs. These methods facilitate both the modeling and analysis of motions, and have enabled the study of complex and high-dimensional problems in both robotic and molecular domains. In order to efficiently study biologically relevant molecular folding behaviors we have developed new techniques based on Monte Carlo solution, master equation calculation, and non-linear dimensionality reduction to run simulations and analysis on the roadmap. The first method, Map-based master equation calculation (MME), extracts global properties of the folding landscape such as global folding rates. On the other hand, another method, Map-based Monte Carlo solution (MMC), can be used to extract microscopic features of the folding process. Also, the application of dimensionality reduction returns a lower-dimensional representation that still retains the principal features while facilitating both modeling and analysis of motion landscapes. A key contribution of our methods is the flexibility to study larger and more complex structures, e.g., 372 residue Alpha-1 antitrypsin and 200 nucleotide ColE1 RNAII. We also applied intelligent roadmap-based techniques to the area of robotic motion. These methods take advantage of unsupervised learning methods at all stages of the planning process and produces solutions in complex spaces with little cost and less manual intervention compared to other adaptive methods. Our results show that our methods have low overhead and that they out-perform two existing adaptive methods in all complex cases studied.Item Multi-layer approach to motion planning in obstacle rich environment(2009-05-15) Kim, Sung HyunA widespread use of robotic technology in civilian and military applications has generated a need for advanced motion planning algorithms that are real-time implementable. These algorithms are required to navigate autonomous vehicles through obstacle-rich environments. This research has led to the development of the multilayer trajectory generation approach. It is built on the principle of separation of concerns, which partitions a given problem into multiple independent layers, and addresses complexity that is inherent at each level. We partition the motion planning algorithm into a roadmap layer and an optimal control layer. At the roadmap layer, elements of computational geometry are used to process the obstacle rich environment and generate feasible sets. These are used by the optimal control layer to generate trajectories while satisfying dynamics of the vehicle. The roadmap layer ignores the dynamics of the system, and the optimal control layer ignores the complexity of the environment, thus achieving a separation of concern. This decomposition enables computationally tractable methods to be developed for addressing motion planning in complex environments. The approach is applied in known and unknown environments. The methodology developed in this thesis has been successfully applied to a 6 DOF planar robotic testbed. Simulation results suggest that the planner can generate trajectories that navigate through obstacles while satisfying dynamical constraints.Item Multi-robot Caravanning(2013-11-06) Mahadevan, AdityaWe study multi-robot caravanning, which is loosely defined as the problem of a heterogeneous team of robots visiting specific areas of an environment (waypoints) as a group. After formally defining this problem, we propose a novel solution that requires minimal communication and scales with the number of waypoints and robots. Our approach restricts explicit communication and coordination to occur only when robots reach waypoints, and relies on implicit coordination when moving between a given pair of waypoints. At the heart of our algorithm is the use of leader election to e?ciently exploit the unique environmental knowledge available to each robot in order to plan paths for the group, which makes it general enough to work with robots that have heterogeneous representations of the environment. We implement our approach both in simulation and on a physical platform, and characterize the performance of the approach under various scenarios. We demonstrate that our approach can successfully be used to combine the planning capabilities of di?erent agents.Item Precision mechatronics lab robot development(2009-05-15) Rogers, Adam GregoryThis thesis presents the results from a modification of a previously existing research project titled the Intelligent Pothole Repair Vehicle (IPRV). The direction of the research in this thesis was changed toward the development of an industrially based mobile robot. The principal goal of this work was the demonstration of the Precision Mechatronics Lab (PML) robot. This robot should be capable of traversing any known distance while maintaining a minimal position error. An optical correction capability has been added with the addition of a webcam and the appropriate image processing software. The primary development goal was the ability to maintain the accuracy and performance of the robot with inexpensive and low-resolution hardware. Combining the two abilities of dead-reckoning and optical correction on a single platform will yield a robot with the ability to accurately travel any distance. As shown in this thesis, the additional capability of off-loading its visual processing tasks to a remote computer allows the PML robot to be developed with less expensive hardware. The majority of the literature research presented in this paper is in the area of visual processing. Various methods used in industry to accomplish robotic mobility, optical processing, image enhancement, and target interception have been presented. This background material is important in understanding the complexity of this field of research and the potential application of the work conducted in this thesis. The methods shown in this research can be extended to other small robotic vehicles, with two separate drive wheels. An empirical method based upon system identification was used to develop the motion controllers. This research demonstrates a successful combination of a dead-reckoning capability, an optical correction method, and a simplified controller methodology capable of accurate path following. Implementation of this procedure could be extended to multiple and inexpensive robots used in a manufacturing setting.