If you have ever hiked up a steep hill to reach a viewpoint, you will know that sensing can involve the expenditure of effort. More generally, the choice of which movement an intelligent system chooses to make is usually based on information gleaned from sensors. But the information required to make the motion decision may not be immediately to hand, so the system . first has to plan a motion whose purpose is to acquire the needed sensor information. Again, this conforms to our everyday experience: I am in the woods and don't know which direction to go, so I climb up to the ridge to get my bearings; I am lost in a new town, so I plan to drive to the next junction where there is sure to be a roadsign, failing that I will ask someone who seems to be from the locality. Why, if experiences such as these are so familiar, has the problem only recently been recognised and studied in Robotics? One reason is that until quite recently Robotics research was dominated by work on robot arms with limited reach and fixed in a workcell.

If you have ever hiked up a steep hill to reach a viewpoint, you will know that sensing can involve the expenditure of effort. More generally, the choice of which movement an intelligent system chooses to make is usually based on information gleaned from sensors. But the information required to make the motion decision may not be immediately to hand, so the system . first has to plan a motion whose purpose is to acquire the needed sensor information. Again, this conforms to our everyday experience: I am in the woods and don't know which direction to go, so I climb up to the ridge to get my bearings; I am lost in a new town, so I plan to drive to the next junction where there is sure to be a roadsign, failing that I will ask someone who seems to be from the locality. Why, if experiences such as these are so familiar, has the problem only recently been recognised and studied in Robotics? One reason is that until quite recently Robotics research was dominated by work on robot arms with limited reach and fixed in a workcell.

This book constitutes the thoroughly refereed post-proceedings of the International Workshop on Sensor Based Intelligent Robots held in Dagstuhl Castle, Germany, in October 2000.The 20 revised full papers were carefully reviewed and improved for inclusion in this book. Addressing a broad variety of aspects of the highly interdisciplinary field of robotics, the book presents three topical sections on sensing, robotics, and intelligence.

The collection of articles presented here, emerged from the Block Island Workshop on Vision and Control that brought together pioneering researchers from around the world. Discussions of new theoretical developments and the empirical validation of techniques and applications, are recorded in this book. Over recent years, robotics, computer vision and control theory researchers have addressed theoretical issues of: real-time vision, visual tracking, the active focus of attention and vision-based control of motion. At the same time, these theoretical insights have been used in applications such as: vision-based autonomous driving, vision-based grasping, human-computer interfaces, control of MEMS systems and medical image processing. From this book the reader will gain an overview of the latest thinking in vision and control, as well as an introduction to many of the techniques used in this area.