Sensor Fusion-Based Semantic Map Building

Vision-Based Semantic-Map Building and Localization

A semantic-map building method is proposed to localize a robot in the semantic-map. Our semantic-map is organized by using SIFT feature-based object representation. In addition to semantic map, a vision-based relative localization is employed as a process model of extended Kalman filters, where optical flows and Levenberg-Marquardt least square minimization are incorporated to predict relative ...

Sensor fusion and map building for underwater navigation

Somajyoti Majumder Australian Centre for Field Robotics(ACFR) University of Sydney Rose Street Building (J04) Sydney, NSW 2006 Australia Steve Scheding Australian Centre for Field Robotics(ACFR) University of Sydney Rose Street Building (J04) Sydney, NSW 2006 Australia Hugh Durrant-Whyte Australian Centre for Field Robotics(ACFR) University of Sydney Rose Street Building (J04) Sydney, NSW 2006 ...

Semantic Grid Map Building

Conventional Occupancy Grid (OG) map which contains occupied and unoccupied cells can be enhanced by incorporating semantic labels of places to build semantic grid map. Map with semantic information is more understandable to humans and hence can be used for efficient communication, leading to effective human robot interactions. This paper proposes a new approach that enables a robot to explore ...

A Correction System of Odometry Error for Map Building of Mobile Robot Based on Sensor fusion

Map Building of Unknown Environment Based on Fuzzy Sensor Fusion of Ultrasonic Ranging Data

This paper investigates the use of ranging data collected from ultrasonic sensors mounted on a two-wheeled mobile robot, Pioneer 3-DX, to build an occupancy grid map for an unknown indoor environment based on fuzzy sensor fusion of the ultrasonic ranging data. Because of uncertainties inevitably encountered by using the ultrasonic sensors, a more reliable sensor model is derived to solve the pr...