Extending the Occupancy Grid Concept for Low-Cost Sensor-Based SLAM

The simultaneous localization and mapping problem is approached by using an ultrasound sensor and wheel encoders. To account for the low precision inherent in ultrasound sensors, the occupancy grid notion is extended. The extension takes into consideration with which angle the sensor is pointing, to compensate for the issue that an object is not necessarily detectable from all positions due to deficiencies in how ultrasonic range sensors work. A mixed linear/nonlinear model is derived for future use in Rao-Blackwellized particle smoothing.