Localisation, the ability to find out the position, is essential to a mobile robot. The most common localisation method is to use a Kalman filter to fuse the data from dead reckoning data with the observations of environment features. The different artificial landmarks have been introduced to correct the error of dead reckoning, including visual landmark based methods. Since multiple landmarks ...

This paper presents a method for correcting dead reckoning parameters, which are heading and step size, for a pedestrian navigation system. In this method, the compass bias error and the step size error can be estimated during the period that the global positioning system (GPS) signal is available. The errors are used for correcting those parameters to improve the accuracy of position determina...

Aimed at the demand of positioning in complicated environments such as indoor and built-up areas, the method of autonomous navigation positioning and orientation based on an adaptive step length model was proposed in this paper. Using an accelerometer placed on the human waist, stride was recognized and the relationship between the step length, stride factor, and walking speed was established. ...

Localization is an essential part of any autonomous vehicle. In a simple setting, the localization problem is almost trivial, and can be solved sufficiently using simple dead reckoning or an off-the-shelf GPS with differential corrections. However, as the surroundings become more complex, so does the localization problem. The urban environment is a prime example of a situation in which a vehicl...

Route taken and distance travelled are important parameters for studies of animal locomotion. They are often measured using a collar equipped with GPS. Collar weight restrictions limit battery size, which leads to a compromise between collar operating life and GPS fix rate. In studies that rely on linear interpolation between intermittent GPS fixes, path tortuosity will often lead to inaccurate...

We study task partitioning in the context of swarm robotics. Task partitioning is the decomposition of a task into subtasks that can be tackled by different workers. We focus on the case in which a task is partitioned into a sequence of subtasks that must be executed in a certain order. This implies that the subtasks must interface with each other, and that the output of a subtask is used as in...