Browsing by Author "Williams, Joshua Murry"
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Item Automated conceptual design of manufacturing workcells in radioactive environments(2013-08) Williams, Joshua Murry; Landsberger, Sheldon; Pryor, Mitchell WayneThe design of manufacturing systems in hazardous environments is complex, requiring interdisciplinary knowledge to determine which components and operators (human or robotic) are feasible. When conceptualizing designs, some options may be overlooked or unknowingly infeasible due to the design engineers' lack of knowledge in a particular field or ineffective communication of requirements between disciplines. To alleviate many of these design issues, we develop a computational design tool to automate the synthesis of conceptual manufacturing system designs and optimization of preliminary layouts. To generate workcell concepts for manufacturing processes, we create a knowledge-based system (KBS) that performs functional modeling using a common language, a generic component database, and a rule set. The KBS produces high-level task plans for specific manufacturing processes and allocates needed material handling tasks between compatible human and/or robotic labor. We develop an extended pattern search (EPS) algorithm to optimize system layouts based on worker dose and cycle time minimization using the functions and sequencing of generated task plans. The KBS and EPS algorithm were applied to the design of glovebox processing systems at Los Alamos National Laboratory (LANL). Our computational design tool successfully generates design concepts with varied task allocation and processing sub-tasks and layouts with favorable manipulation workspaces. This work establishes a framework for automated conceptual design while providing designers with a beneficial tool for designing manufacturing systems in an interdisciplinary and highly constrained domain.Item Improved manipulator configurations for grasping and task completion based on manipulability(2010-12) Williams, Joshua Murry; Pryor, Mitchell Wayne; Landsberger, SheldonWhen a robotic system executes a task, there are a number of responsibilities that belong to either the operator and/or the robot. A more autonomous system has more responsibilities in the completion of a task and must possess the decision making skills necessary to adequately deal with these responsibilities. The system must also handle environmental constraints that limit the region of operability and complicate the execution of tasks. There are decisions about the robot’s internal configuration and how the manipulator should move through space, avoid obstacles, and grasp objects. These motions usually have limits and performance requirements associated with them. Successful completion of tasks in a given environment is aided by knowledge of the robot’s capabilities in its workspace. This not only indicates if a task is possible but can suggest how a task should be completed. In this work, we develop a grasping strategy for selecting and attaining grasp configurations for flexible tasks in environments containing obstacles. This is done by sampling for valid grasping configurations at locations throughout the workspace to generate a task plane. Locations in the task plane that contain more valid configurations are stipulated to have higher dexterity and thus provide greater manipulability of targets. For valid configurations found in the plane, we develop a strategy for selecting which configurations to choose when grasping and/or placing an object at a given location in the workspace. These workspace task planes can also be utilized as a design tool to configure the system around the manipulator’s capabilities. We determine the quality of manipulator positioning in the workspace based on manipulability and locate the best location of targets for manipulation. The knowledge of valid manipulator configurations throughout the workspace can be used to extend the application of task planes to motion planning between grasping configurations. This guides the end-effector through more dexterous workspace regions and to configurations that move the arm away from obstacles. The task plane technique employed here accurately captures a manipulator’s capabilities. Initial tests for exploiting these capabilities for system design and operation were successful, thus demonstrating this method as a viable starting point for incrementally increasing system autonomy.