[...]... distinguished © 2006 by Taylor & Francis Group, LLC FRANKL: “dk6033_c001” — 2006/3/31 — 16:42 — page 7 — #7 8 Autonomous Mobile Robots TABLE 1.1 Classes of UGV Class Searcher (TGV) Donkey (SAP/F) kph 40 Wingman (PC-AGV) 100 Hunter-killer (NC-AGV) 120 Capability gaps All-weather sensors Localization and mapping algorithms Long-range sensors and sensors for classifying vegetation Multiple sensors and fusion... University of Illinois Urbana-Champaign, Illinois Sesh Commuri School of Electrical & Computer Engineering University of Oklahoma Norman, Oklahoma Jay A Farrell Department of Electrical Engineering University of California Riverside, California Rafael Fierro MARHES Laboratory School of Electrical & Computer Engineering Oklahoma State University Norman, Oklahoma Shuzhi Sam Ge Department of Electrical and Computer... hierarchical levels has different spatial and temporal resolution The details of a world model are as follows: Low resolution obstacle map and elevation map The obstacle map consists of a 2D array of cells [24] Each cell of the map represents one of the following situations: traversable, obstacle (positive and negative), undefined (such as blind spots), potential hazard, and so forth In addition, high-level... Adams School of Electrical and Electronic Engineering Nanyang Technological University Singapore James S Albus National Institute of Standards and Technology Gaithersburg, Maryland Alessandro Astolfi Electrical and Electronics Engineering Department Imperial College London London, UK Stephen Balakirsky Intelligent Systems Division National Institute of Standards and Technology Gaithersburg, Maryland Anthony... Taylor & Francis Group, LLC FRANKL: “dk6033_c001” — 2006/3/31 — 16:42 — page 15 — #15 16 Color camera Modeling and calibration Task-specific processing Road model Lane Model Vehicle model Terrain model Color segmentation Landmark detection Target tracking Terrain classification Color calibration Stereo calibration Vehicle to world coordinates Obstacle detection 3D target tracking Terrain analysis Stereo... Jiali Shen II Modeling and Control 187 Chapter 5 Stabilization of Nonholonomic Systems 191 Alessandro Astolfi Chapter 6 Adaptive Neural-Fuzzy Control of Nonholonomic Mobile Robots 229 Fan Hong, Shuzhi Sam Ge, Frank L Lewis, and Tong Heng Lee Chapter 7 Adaptive Control of Mobile Robots Including... electrical signal At present, compared to visible light cameras, the resolution is reduced (e.g., 320 × 240 pixels) and the response is naturally slower There are other problems to contend with, such as calibration and drift of the sensor IR cameras are expensive © 2006 by Taylor & Francis Group, LLC FRANKL: “dk6033_c001” — 2006/3/31 — 16:42 — page 9 — #9 10 Autonomous Mobile Robots FIGURE 1.1 A selection... currently in use for road and vehicle following, and for obstacle detection are then reviewed With the wealth of information afforded by various visual sensors, sensor fusion techniques play an important role in exploiting the available information to 1 © 2006 by Taylor & Francis Group, LLC FRANKL: “dk6033_c001” — 2006/3/31 — 16:42 — page 1 — #1 2 Autonomous Mobile Robots further improve the perceptual... page xv — #15 Abstract As technology advances, it has been envisioned that in the very near future, robotic systems will become part and parcel of our everyday lives Even at the current stage of development, semi -autonomous or fully automated robots are already indispensable in a staggering number of applications To bring forth a generation of truly autonomous and intelligent robotic systems that will... include any lens distortion model, they are quick and simple to calculate © 2006 by Taylor & Francis Group, LLC FRANKL: “dk6033_c001” — 2006/3/31 — 16:42 — page 13 — #13 14 Autonomous Mobile Robots 2 Nonlinear optimization techniques account for lens distortion in the camera model through iterative minimization of a determined function The minimizing function is usually the distance between the image . Sarangapani 22. Autonomous Mobile Robots: Sensing, Control, Decision Making and Applications, edited by Shuzhi Sam Ge and Frank L. Lewis DK6033_half-series-title.qxd 2/23/06 8:37 AM Page C © 2006 by Taylor. international journals. He is also serving as a technical consultant for the local industry. Frank L. Lewis, IEEE Fellow, PE Texas, is a distinguished scholar professor and Moncrief-O’Donnell chair. artificial intelligence, control theory and robotics, autonomous (land, sea, and air) vehicles, and numerous other discip- lines. The technology involved is highly complex and multidisciplinary,