Image Understanding and Robotics Research at Columbia University

The research investigations of the Vision/Robotics Laboratory at Columbia University reflect the diversity of interests of its four faculty members, two staff programmers and 15 Ph.D. students. Several of the projects involve either a visiting computer science post-doc, other faculty members in the department or the university, or researchers at AT&T Bell Laboratories or Philips laboratories. We list below a summary of our interest and results, together with the principal researchers associated with them. Since it is difficult to separate those aspects of robotic research that are purely visual from those that are vision-like (for example, tactile sensing) or vision-related (for example, integrated vision-robotic systems), we have listed all robotic research that is not purely manipulative

Hybrid Intelligent System for Diagnosing Breast Pre-Cancerous and Cancerous Conditions Based on Image Analysis

Modern diagnostic technologies are automated microscopy systems (AMSs). In this research study, the authors analyzed the modern AMS methods and algorithms. Criteria-based comparative analysis of AMS has been made, and their advantages and disadvantages have been identified at the three main levels of image processing. This allowed determining the main direction of such systems development, that is, designing the hybrid intelligent AMS. The work of an expert physician implies visual image interpretation, selection of qualitative features of micro-objects, the formation of diagnostic rules based on expert knowledge, and making diagnoses. Knowledge introduction model contains a productive model, in which knowledge is presented in the form of rules expressed in productive pseudo code if-then. Logic inference machine is a module designed to logically derive the facts and rules from the base according to the laws of formal logic. A set of modern methods and algorithms for low-, mid-, and high-level image processing have been used in the AMS structure

NASA Center for Intelligent Robotic Systems for Space Exploration

NASA's program for the civilian exploration of space is a challenge to scientists and engineers to help maintain and further develop the United States' position of leadership in a focused sphere of space activity. Such an ambitious plan requires the contribution and further development of many scientific and technological fields. One research area essential for the success of these space exploration programs is Intelligent Robotic Systems. These systems represent a class of autonomous and semi-autonomous machines that can perform human-like functions with or without human interaction. They are fundamental for activities too hazardous for humans or too distant or complex for remote telemanipulation. To meet this challenge, Rensselaer Polytechnic Institute (RPI) has established an Engineering Research Center for Intelligent Robotic Systems for Space Exploration (CIRSSE). The Center was created with a five year $5.5 million grant from NASA submitted by a team of the Robotics and Automation Laboratories. The Robotics and Automation Laboratories of RPI are the result of the merger of the Robotics and Automation Laboratory of the Department of Electrical, Computer, and Systems Engineering (ECSE) and the Research Laboratory for Kinematics and Robotic Mechanisms of the Department of Mechanical Engineering, Aeronautical Engineering, and Mechanics (ME,AE,&M), in 1987. This report is an examination of the activities that are centered at CIRSSE