Personal robotics applications require autonomous mobile robot navigation methods that are safe and robust. Two requirements are an automatic motion planner to select paths and a robust way of ensuring that the robot can follow the selected path given the unavoidable odometer and control errors. This book first describes a roadmap-based path planning method that is suitable for partially known indoor environments and requires only inexpensive range sensors. Next, we present a new sector-based localizer that is robust in the presence of sensor limitations and unknown obstacles while still maintaining computational efficiency. We extend our approach to teams of robots focusing on quickly sensing ranges from all robots while avoiding sensor cross-talk, and reducing the pose uncertainties of all robots while using a minimal number of sensing rounds.

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