Automated Assembly Using Feature Localization

Automated assembly of mechanical devices is studies by researching methods of operating assembly equipment in a variable manner; that is, systems which may be configured to perform many different assembly operations are studied. The general parts assembly operation involves the removal of alignment errors within some tolerance and without damaging the parts. Two methods for eliminating alignment errors are discussed: a priori suppression and measurement and removal. Both methods are studied with the more novel measurement and removal technique being studied in greater detail. During the study of this technique, a fast and accurate six degree-of-freedom position sensor based on a light-stripe vision technique was developed. Specifications for the sensor were derived from an assembly-system error analysis. Studies on extracting accurate information from the sensor by optimally reducing redundant information, filtering quantization noise, and careful calibration procedures were performed. Prototype assembly systems for both error elimination techniques were implemented and used to assemble several products. The assembly system based on the a priori suppression technique uses a number of mechanical assembly tools and software systems which extend the capabilities of industrial robots. The need for the tools was determined through an assembly task analysis of several consumer and automotive products. The assembly system based on the measurement and removal technique used the six degree-of-freedom position sensor to measure part misalignments. Robot commands for aligning the parts were automatically calculated based on the sensor data and executed.

Modeling Robot Dynamic Performance for Endpoint Force Control

This research aims to understand the fundamental dynamic behavior of servo-controlled machinery in response to various types of sensory feedback. As an example of such a system, we study robot force control, a scheme which promises to greatly expand the capabilities of industrial robots by allowing manipulators to interact with uncertain and dynamic tasks. Dynamic models are developed which allow the effects of actuator dynamics, structural flexibility, and workpiece interaction to be explored in the frequency and time domains. The models are used first to explain the causes of robot force control instability, and then to find methods of improving this performance.

Safe Distributed Coordination of Heterogeneous Robots through Dynamic Simple Temporal Networks

Research on autonomous intelligent systems has focused on how robots can robustly carry out missions in uncertain and harsh environments with very little or no human intervention. Robotic execution languages such as RAPs, ESL, and TDL improve robustness by managing functionally redundant procedures for achieving goals. The model-based programming approach extends this by guaranteeing correctness of execution through pre-planning of non-deterministic timed threads of activities. Executing model-based programs effectively on distributed autonomous platforms requires distributing this pre-planning process. This thesis presents a distributed planner for modelbased programs whose planning and execution is distributed among agents with widely varying levels of processor power and memory resources. We make two key contributions. First, we reformulate a model-based program, which describes cooperative activities, into a hierarchical dynamic simple temporal network. This enables efficient distributed coordination of robots and supports deployment on heterogeneous robots. Second, we introduce a distributed temporal planner, called DTP, which solves hierarchical dynamic simple temporal networks with the assistance of the distributed Bellman-Ford shortest path algorithm. The implementation of DTP has been demonstrated successfully on a wide range of randomly generated examples and on a pursuer-evader challenge problem in simulation.

Lean Transition of Emerging Industrial Capability

This volume of the final report documents the technical work performed from December 1998 through December 2002 under Cooperative Agreement F33615-97-2-5153 executed between the U.S. Air Force, Air Force Research Laboratory, Materials and Manufacturing Directorate, Manufacturing Technology Division (AFRL/MLM) and the McDonnell Douglas Corporation, a wholly-owned subsidiary of The Boeing Company. The work was accomplished by The Boeing Company, Phantom Works, Huntington Beach, St. Louis, and Seattle; Ford Motor Company; Integral Inc.; Sloan School of Management in the Massachusetts Institute of Technology; Pratt & Whitney; and Central State University in Xenia, Ohio and in association with Raytheon Corporation. The LeanTEC program manager for AFRL is John Crabill of AFRL / MLMP and The Boeing Company program manager is Ed Shroyer of Boeing Phantom Works in Huntington Beach, CA. Financial performance under this contract is documented in the Financial Volume of the final report.

Lean Transition of Emerging Industrial Capability (LeanTEC)

Lean Transition of Emerging Industrial Capability (LeanTEC) program was a cooperative agreement between the Boeing Company and AFRL conducted from January 1998 to January 2002. The results of this program are documented in the Manual for Effective Technology Transition Processes included as an attachment to this report. This manual provides processes, procedures, and tools for greatly improving technology transition in the aerospace industry. Methodology for the implementation of these improvements is given along with methods for customizing the various processes, procedures, and tools for a given company or business unit. The indicated methodology was tested by the LeanTEC team and results are documented in the report.

Industrial Relations and "Humanware"

This is a preliminary paper. Please do not quote without the permission of the author. The research on which this paper is based has been conducted with the collaboration of John Paul MacDuffie, MIT. The researchers owe much to the warm cooperation of managers, employees, and union officials of Japanese auto companies and joint venture companies in the U.S. as well as American auto companies and the UAW. We would like to express our sincere appreciation for their assistance.