Abstract This paper compares a differential wheelspeed based dead reckoning system to a gyro based system for land navigation. Test results show that the gyro and wheelspeed-heading schemes perform equally well when modeling assumptions hold, such as when navigating smooth road surfaces. However, the wheelspeed-heading estimator’s position errors grow about twice as fast as the gyro based syste...

Mobile robot navigation and localization is frequently aided by, or even dependent upon, a good estimate of the rate of dead-reckoning error accumulation. Sensor data can be used for position estimation, but this often involves overhead in acquiring and processing the data. By sensing and then classifying the surface type, an estimate of the rate of error accumulation for dead-reckoning allows ...

Mobile robot navigation and localization is frequently aided by, or even dependent upon, a good estimate of the rate of dead-reckoning error accumulation. Sensor data can be used for position estimation, but this often involves overhead in acquiring and processing the data. By sensing and then classifying the surface type, an estimate of the rate of error accumulation for dead-reckoning allows ...

The state-of-the-art approach to realize consistency in distributed virtual environments (e.g., action games, multi-user virtual reality, and battlefield simulations) is dead reckoning. A fundamental problem of dead reckoning is that participants may perceive different states for the same entity. While these inconsistencies will eventually be repaired, the resulting state of an entity may be in...

To combine sensor information from distributed robot teams, it is critical to know the locations of all the robots relative to each other. This paper presents a novel fault tolerant localization algorithm developed for centimeterscale robots, called Millibots. To determine their locations, the Millibots measure the distances between themselves with an ultrasonic distance sensor. They then combi...

This paper presents an aided dead-reckoning navigation structure and signal processing algorithms for self localization of an autonomous mobile device by fusing pedestrian dead reckoning and WiFi signal strength measurements. WiFi and inertial navigation systems (INS) are used for positioning and attitude determination in a wide range of applications. Over the last few years, a number of low-co...

This work presents a combination of a teach-and-replay visual navigation and Monte Carlo localization methods. It improves a reliable teach-and-replay navigation method by replacing its dependency on precise dead-reckoning by introducing Monte Carlo localization to determine robot position along the learned path. In consequence, the navigation method becomes robust to dead-reckoning errors, can...