This paper presents a sensor fusion framework that improves the localization of mobile
robots with limited computational resources. It employs an event based Kalman Filter to …

The ability of an autonomous unmanned aerial vehicle to navigate and fly precisely
determines its utility and performance. The current navigation systems are highly dependent …

This paper presents a local sensor fusion technique with an event-based global position
correction to improve the localization of a mobile robot with limited computational resources …

The area of cognitive or intelligent robotics is moving from the single monolithic robot control
and behavior problem to that of controlling robots with multiple components or multiple …

Nowadays, smart mobile devices include more and more sensors on board, such as motion
sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators …

This paper presents a Hybrid filter based Simultaneous Localization and Mapping (SLAM)
scheme for a mobile robot to compensate for the Extended Kalman Filter (EKF) based SLAM …

Developing an autonomous indoor mobile robot navigation system from scratch is very
difficult and it takes a long time. It requires a series of complex tasks such as handling given …

Self-localization is a fundamental requirement for autonomous mobile robots. With the rapid
development in sensor technology, the sensor suites of robot provide multimodal information …

Extended Kalman Filter (EKF) has been a popular approach in localization of a mobile robot.
However, the performance of the EKF and the quality of the estimation depends on the …

Particle filter (PF) is widely used in mobile robot localization, since it is suitable for the
nonlinear non-Gaussian system. Localization based on PF, However, degenerates over …