Integrated On-Line Localization, Mapping and Coverage Algorithm of Unknown Environments for Robotic Vacuum Cleaners Based on Minimal Sensing
- 1 January 2011
- journal article
- Published by Taylor & Francis Ltd in Advanced Robotics
- Vol. 25 (13-14), 1651-1673
- https://doi.org/10.1163/016918611x584622
Abstract
This paper presents a new complete coverage algorithm of a robotic vacuum cleaner (RVC) with a low-cost sensor in an unknown environment. To achieve complete coverage, the RVC must have navigation systems for precise position estimation with localization and a prior map or a map using information that has been continuously collected from the environment. To do this, two-dimensional laser range finders and vision sensors are becoming increasingly popular in mobile robotics, and various methods using sensors like these have been introduced by many researchers. However, it is difficult to apply the methods to sensors used in most RVCs due to their constraints. In this paper, we present a new method applied to most RVCs. For developing the method, we considered the two main problems of maintaining low computational load, and coping with low-cost sensor systems with limited range, detection uncertainty and measurement error. To solve the problems, we propose an assumption that major structures of an indoor environment are rectilinear, and can be represented by sets of parallel and perpendicular lines. Then we derive an algorithm that uses this assumption to map the environment, localize the robot and plan the coverage path with a new cellular decomposition approach. Simulation and experiments verify that the proposed method guarantees complete coverage.Keywords
This publication has 17 references indexed in Scilit:
- Complete Coverage Navigation of Cleaning Robots Using Triangular-Cell-Based MapIEEE Transactions on Industrial Electronics, 2004
- Mobile-robot navigation with complete coverage of unstructured environmentsRobotics and Autonomous Systems, 2004
- A Neural Network Approach to Complete Coverage Path PlanningIEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2004
- Adapting the Sample Size in Particle Filters Through KLD-SamplingThe International Journal of Robotics Research, 2003
- Path Planning for Robotic Demining: Robust Sensor-Based Coverage of Unstructured Environments and Probabilistic MethodsThe International Journal of Robotics Research, 2003
- Probabilistic roboticsCommunications of the ACM, 2002
- A terrain-covering algorithm for an AUVAutonomous Robots, 1996
- Mobile robot localization by tracking geometric beaconsIEEE Transactions on Robotics and Automation, 1991
- Dynamic path planning in sensor-based terrain acquisitionIEEE Transactions on Robotics and Automation, 1990
- A numerically stable dual method for solving strictly convex quadratic programsMathematical Programming, 1983