Download PDF Intelligent Robots and Systems by Volker Graefe

Sinopsis

A new type of actively sensing multisonar system has been developed for obstacle detection, localization and map updating in indoor environments. It comprises 24 individual intelligent transmitter and receiver elements arranged in a horizontal plane around a high-speed motion platform. The physical sensors are electronically configured to form various types of virtual sensor arrays for specific tasks and situations. A method for high-frequency firing compensates for the low speed of sound in air. Various schemes for intelligent evaluation of the array outputs provide highly accurate localization estimates. Experiments with the developed multisonar system in structured and cluttered environments demonstrate improved perception capabilities compared to state-of-the-art approaches

Content

1. SENSING AND PERCEPTION
2. A new High-performance Multisonar System for Fast Mobile Robot Applications
3. Proper Selection of Sonar and Visual Sensors in Vehicle Detection and Avoidance
4. Selective Refinement of 3-D Scene Description by Attentive Observation for Mobile Robot
5. Active Vision Inspired by Mammalian Fixation Mechanism
6. Realtime Range Imaging Using An Adjustment-free Photo VLSI
7. A Pedestrian Discrimination Method Based on Rhythm
8. Visual Recognition of Obstacles on Roads
9. Visual Collision Avoidance by Segmentation
10. LEARNING AND PLANNING
11. Using Perceptions to Plan Incremental Adaptions
12. Robot Task Programming by Human Demonstration: Mapping Human Grasps to Manipulator Grasps
13. Robot Learning By Nonparametric Regression
14. Behavioral Control in Mobile-Robot Navigation Using a Fuzzy Decision Making Approach
15. Learning Emergent Tasks for an Autonomous Mobile Robot
16. Efficient Reinforcement Learning of Navigation Strategies in an Autonomous Robot
17. A Lifelong Learning Perspective for Mobile Robot Control
18. A Multilevel Learning Approach to Mobile Robot Path Planning
19. A Self-Organizing Representation of Sensor Space for Mobile Robot Navigation
20. Path Planning and Guidance Techniques for an Autonomous Mobile Cleaning Robot
21. MANIPULATION
22. Grasp Strategies for a Dextrous Robotic Hand
23. Motion Scheme for Dextrous Manipulation in the Intelligent Cooperative Manipulation System - ICMS
24. Designing a Behavior of a Mobile Robot Equipped with a Manipulator to Open and Pass through a Door
25. The Development of Re-usable Software Systems for Intelligent Autonomous Robots in Industrial and Space Applications
26. TELEROBOTICS AND SPACE ROBOTICS
27. Toward Integrated Operator Interface for Advanced Teleoperation under Time-Delay
28. Active Understanding of Human Intention by a Robot through Monitoring of Human Behavior
29. Human/machine Sharing Control for Telerobotic Systems
30. Task-Directed Programming of Sensor-Based Robots
31. Telerobotics with Large Time Delays - the ROTEX Experience
32. Feature-Based Visual Servoing and its Application to Telerobo
33. Practical Coordination Control Between Satellite Attitude and Manipulator Reaction Dynamics Based on Computed Momentum Concept
34. A 5-Axis Mini Direct Drive Robot for Teleoperation and Biotechnology
35. A Laboratory Test Bed for Space Robotics: The VES II
36. MULTIPLE ROBOTS
37. Hierarchical Prediction Model for Intelligent Communication in Multiple Robotic Systems
38. Proposal for Cooperative Robot "Gunryu" Composed of Autonomous Segments
39. Unified Control for Dynamic Cooperative Manipulation
40. MOBILE ROBOT SYSTEMS
41. Comparative Study of Adaptive Controllers for a Pneumatic Driven Leg
42. An Efficient Forward Gait Control for a Quadruped Walking Robot
43. The Six-Legged TUM Walking Robot
44. Vision-Based Adaptive and Interactive Behaviors in Mechanical Animals Using the Remote-Brained Approach
45. ROBOTICS IN MEDICINE
46. Planning, Calibration and Collision-Avoidance for Image-Guided Radiosurgery

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Download PDF Cells and Robots Modeling and Control of Large-Size Agent Populations by Dejan Lj. Milutinovi´c

Sinopsis

Understanding development and functions of living organisms continuously occupies the attention of science. Consequently, mathematical modeling of biological systems is a recurrent topic in research. Recently, this field has become even more attractive due to technological improvements on data acquisition that provide researchers a further insight into such systems. Technology to read DNA sequences, or to observe protein structures along with a variety of microscopy methods, has enabled collecting large amounts of data around and inside the cell, classically considered as the smallest chunk of life.
 

In this book, we are particularly concerned with cells that have an active role protecting living organisms from infections caused by foreign bodies, constituting the immune system. The role of the immune system is to continuously monitor the organism, to recognize an invader, to generate a response that will clear the invader and to help healing the damaged tissues. The major components of this chain of action are motile cells. Cells motility1 is a property intrinsic to their function, i.e., to fight against infections in the right place at the right time during an immune response. While we are quite certain about the places where cells are produced and where they reside during their life cycle, the question of how they modulate their motion and bio-chemical activity against external stimuli still presents an active field of research.
 

Apparently, the immune system cells are autonomous agents. On the other hand, an autonomous mobile robot can be seen as the most natural mechanic analogy of the cell. Hence, we find studies about the cell bio-chemical signal processing, intercellular communication and cell reactive behavior in close relation to signal processing, communication and control for mobile robots. Investigation of the cell-robot analogy has the potential to influence future biological research, but also to provide the guidelines for the development of a systembased approach to describe and analyze complex multi-agent/robot systems.

Content

1.  Introduction
2. Immune System and T-Cell Receptor Dynamics of a T-Cell Population
3. Micro-Agent and Stochastic Micro-Agent Models
4. Micro-Agent Population Dynamics
5. Stochastic Micro-Agent Model of the T-Cell Receptor Dynamics
6. Stochastic Micro-Agent Model Uncertainties
7. Stochastic Modeling and Control of a Large-Size Robotic Population
8. Conclusions and Future Work
9. Stochastic Model and Data Processing of Flow Cytometry Measurements
10. Estimated T-Cell Receptor Probability Density Function
11. Steady State T-Cell Receptor Probability Density Function and Average Amount
12. Optimal Control of Partial Differential Equations

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Download PDF CNC Robotics Build Your Own Workshop Bot by Geoff Williams

Sinopsis

I first th ought about adding a CNC router to my too l collection after finishing a kitchen cabinet renovation in my home. I refaced the cabinets and bui lt 26 new doors. during which I discovered that door building can become monotonou s at best. As always happens when you tell or show yo ur friends and family what you have done, someone wi ll have a similar project and enlist your help . That someone was my friend Geoff S. He wanted to do the same thing to his kitchen-reface and install new cabinet doors. I agreed to help him and he decided on a style of door that can be made from one piece of material cut to size and routed to create the look he wanted . Of course the prospect of bu ilding a who le Jot of doors and making templates to facilitate the routing wasn't too thrilling. That's when I thought a small CNC machine would come in handy. All th e repetitive routing could be asslgned to the CNC machine and the doors would more closely resemble each other once human error had been removed from the equation. Now the project didn't seem too bad at all!

Content

1. Design
2. Electronics
3. Making the Printed Circuit Board
4. Driver Assembly
5. Softwa re Setup and Driver Testing
6. The Frame
7. The Gantry and X-axis
8. The Z and Y Axes
9. Motor and Lead Screw Installation
10. File Creation and KCam
11. Tool Holders and Testing
12. Examples
13. Sources of Material

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