Automatic Task Planning for Robot Vision

Abstract

This paper describes an automated planner for visual inspection and monitoring tasks using a robot mounted CCD camera. It is capable of finding heuristically near-optimal viewing positions for a series of visual tasks, and of ordering them and planning robot paths between them to produce a near minimal cost overall task plan for the sequence. It has been optimized for intervention-style tasks with relatively large, cluttered workspaces, where it is difficult for a human operator to take account of all the constraints involved. The guiding principle of the work has been to aim for reliability by using quantitative, physically-based measures of quality wherever possible, and by using global search to ensure that possible solutions are not overlooked. We discuss a novel global function optimization technique based on decision theory and subjective models of function behaviour, that allows global viewpoint searches to run in the time usually required for local ones.

Evolutionary Computation for Sensor Planning: The Task Distribution Plan

“…The MVP system developed by Abrams et al [8] considered the viewpoint planning of one manipulator monitoring the movements of a second robot. The work developed by Triggs and Laugier [9] considers workspace constraints of a robot carrying a camera with the goal of automated inspection. More recently, Whaite and Ferrie [10] developed an uncertainty based approach for autonomous exploration using a manipulator robot.…”

Multiple robot task distribution: towards an autonomous photogrammetric system

“…The MVP system developed by Tarabanis et al (1993) considered the viewpoint planning of one manipulator monitoring the movements of a second robot. The work developed by Triggs and Laugier (1995) considers workspace constraints of a robot carrying a camera with the goal of automated inspection. Roberts and Marshall (1997) also used a single robot vision system for object recognition instead of accuracy tasks.…”