Books.org participates in affiliate programs including Bookshop.org and the Amazon Services LLC Associates Program. We may earn a commission from qualifying purchases made through links on this page, at no additional cost to you.
Overview
Spatial reasoning and planning is a core constituent in robotics, graphics, computer-aided design, and geographic information systems.After a review of previous work in the related areas, Liu and Daneshmend present here a unified framework for qualitative spatial representation and reasoning, which enables the generation of solutions to spatial problems where the geometric knowledge is imprecise. The approach utilizes qualitative spatial representation and reasoning integrated with a quantitative search procedure based on simulated annealing. Many graphical illustrations and detailed algorithm descriptions help the readers to comprehend the solution paths and to develop their own applications. The book is written as a self-contained text for researchers and graduate students in computer science and related engineering disciplines. The methodologies, algorithmic details, and case studies presented can be used as course material as well as a convenient reference.Synopsis
Spatial reasoning and planning is a core constituent in robotics, graphics, computer-aided design, and geographic information systems.
After a review of previous work in the related areas, Liu and Daneshmend present here a unified framework for qualitative spatial representation and reasoning, which enables the generation of solutions to spatial problems where the geometric knowledge is imprecise. The approach utilizes qualitative spatial representation and reasoning integrated with a quantitative search procedure based on simulated annealing. Many graphical illustrations and detailed algorithm descriptions help the readers to comprehend the solution paths and to develop their own applications.
The book is written as a self-contained text for researchers and graduate students in computer science and related engineering disciplines. The methodologies, algorithmic details, and case studies presented can be used as course material as well as a convenient reference.