Smart Robots

1. Introduction to Smart Robots.- The Book.- Artificial Intelligence and Robots.- Sensing and Effecting.- Knowledge About the Environment.- Interpreting.- Generating.- Reasoning.- Sensors.- Visual Sensors.- Tactile Sensors.- Range Sensors.- Proprioceptors.- Machine Vision.- Manipulators.- Legs.- Arms.- Hands.- Manipulation.- Locomotion.- Natural Language Processing.- Spoken Language.- Expert Systems.- The Future.- 2. Artificial Intelligence for Smart Robots.- The History of Artificial Intelligence.- The Basic Elements of Artificial Intelligence.- Knowledge Representation.- Computational Logic.- Logical Inference.- Common Sense Reasoning.- Non-Deductive Problem Solving Aproaches.- Languages, Tools and Computers.- Applications of Artificial Intelligence.- Principal Participants.- State of the Art.- Basic Core Topics.- Expert Systems.- Natural Language.- Machine Vision.- Towards the Future.- Smart Robots.- Industrial Applications.- Machine Vision.- Expert Systems.- Natural Language.- Computers for Future Automation.- Computer Aided Instruction (CAI).- Learning by Computers.- The Social Impacts.- 3. Smart Robots.- Overview.- Productivity.- Impact on Work Force.- Growth Potential.- System Elements.- Controller.- Manipulator.- End Effector.- Robotic Functional Categories.- Sensory Perception.- Smart Robot Systems.- Application of Smart Robots.- Implementation of Smart Robots into Your Plant.- Research and Development Efforts.- Research Requirements.- Synthesis of Research Needed.- Current Robot Research.- Future Development.- Sensing Devices.- Cost.- Size.- Systems Integration.- Marketing.- Technology.- 4. Sensor-Controlled Robots.- Sensor Integration.- Programming.- Teaching.- Sensitivity.- Proximity Sensors.- Range Sensors.- Tactile Sensors.- Visual Sensors.- Summary.- 5. Machine Vision Systems.- Overview.- Machine Vision Definition.- Origins of Machine Vision.- Relation to Human Vision.- Basis for a General Purpose Image Understanding System.- Basic Paradigms for Machine Vision.- Hierarchical Bottom-Up Approach.- Hierarchical Top-Down Approach.- Heterarchical Approach.- Blackboard Approach.- Levels of Representation.- Representation Methods and Techniques.- Low Level Features.- Extracting Edges and Areas.- Segmentation and Interpretation.- 2-D Representation, Description and Recognition.- Recovery of Intrinsic Surface Characteristics.- Higher Levels of Representation.- Tracking.- Research in Model-Based Machine Vision Systems.- Machine Vision Systems.- General Characteristics.- Machine Vision Inspection Systems.- Machine Vision Recognition and Location Systems.- Commercially Available Machine Vision Systems.- Developers of Machine Vision Systems.- Sources of Research Funding.- Summary of the State of the Art.- Human Vision.- Low and Intermediate Levels of Processing.- Machine Vision System Development.- Current Problems and Issues.- Research Needed.- Future Trends.- Conclusion.- 6. Robot Manipulators.- Configurations.- Jointed Arms.- Cartesian Coordinate.- Cylindrical Coordinate.- Spherical Coordinate.- Actuators.- Work Volume.- Common Work Volume Shape.- Limits on Work Volume.- Optimization.- Robot Controllers.- Dynamic Properties.- Dynamic Performance.- Stability.- Spatial Resolution.- Accuracy.- Repeatability.- Compliance.- 7. Natural Language Processing.- Natural Language Models.- Type A: No World Models.- Type B: Systems that Use Explicit World Models.- Type C: Systems that Include Information about the Goals and Beliefs of Intelligent Entities.- Grammar.- Semantic Processing.- Knowledge representation.- Parsing.- Semantics, Parsing and Understanding.- Natural Language Processing Systems.- Typical System Configurations.- Research Systems Under Development.- Commercial Systems.- Development Facilities.- Complexities of Natural Language Processing.- The Future for Natural Language Processing.- 8. Expert Systems for Robotics.- Fundamentals of Expert Systems.- Expert System Architecture.- The Knowledge Base.- Design Techniques.- Current Expert Systems.- Robotic Applications of Expert Systems.- 9. Computer Integrated Manufacturing.- What is a Computer Integrated Manufacturing System?.- CIMS Benefits.- When to Use CIMS Technology.- Challenges to Management and the Organization.- CIMS Acquisition.- Steps in the Acquisition of a CIMS.- Establishing the CIMS Task Force.- CIMS Implementation Plan.- The Request for Proposal.- Evaluations.- Description of Computer Integrated Manufacturing System Elements.- Detailed Description of a Computer Integrated Manufacturing System.- Work Stations.- Material Handling System.- Control System Software.- Other Significant Elements.- Three Example Computer Integrated Manufacturing Systems.- Kearney and Trecker CIMS at AVCO-Lycoming, Stratford, Connecticut.- Detroit Diesel Allison, Indianapolis, Indiana.- Giddings and Lewis CIMS at Caterpillar Tractor Company, Aurora, Illinois.- Projected Trends in CIMS Technology.- Appendix A: Glossary.- Appendix B: Bibliography.