This paper describes a position estimation tecnique based on the fusion of data obtained by two independent subsystems in a mobile robot navigation context. The rst subsystem is a self-location one composed of an onboard camera, an onboard image processing unit and artiicial landmarks; the second one is a dead-reckoning subsystem based on odometry. The robot navigation system integrates the pos...

In this research we present a Kalman filtering-based motion state estimation method for an autonomous vehicle-trailer system by fusing multiple sensor data, which can be applied directly to autonomous navigation and motion control. The autonomous vehicle-trailer system consists of an autonomous vehicle and a passive trailer which are coupled by a trailer hitch. Our vehicle-trailer system is equ...

This paper presents concepts, methods and experimental results for estimating the scale of a trajectory that is established by monoscopic Visual Odometry algorithms for use in autonomous driving. While monoscopic Visual Odometry has been widely investigated, one of its key issues restrains its broad appliance: the scale drift. To tackle it, we leverage scene inherent information about the groun...

In this paper we present work integrating the robust sequence-based recognition capabilities of the RatSLAM system with the accurate 3D metric properties of a multicamera visual odometry system. The RatSLAM system provides scene sequence recognition capabilities that are not feature dependent, while the multicamera visual odometry system provides accurate and metric 3D motion information which ...

Feature-based visual structure and motion reconstruction pipelines, common in visual odometry and large-scale reconstruction from photos, use the location of corresponding features in different images to determine the 3D structure of the scene, as well as the camera parameters associated with each image. The noise model, which defines the likelihood of the location of each feature in each image...

This paper presents the key steps involved in the design, calibration and error modelling of a low cost odometry system capable of achieving high accuracy dead-reckoning. A consistent error model for estimating position and orientation errors has been developed. Previous work on propagating odometry error covariance relies on incrementally updating the covariance matrix in small time steps. The...

The MagneBike inspection robot is a climbing robot equipped with magnetic wheels. The robot is designed to drive on 3D complexly shaped pipe structures, therefore it is necessary to provide 3D visualization tools for the user who remotely controls the robot out of sight. The localization system is required to provide a 3D map of the unknown environment and the 3D location of the robot in the en...

One of the most important reasons for the popularity of mobile robots in industrial manufacturing is their capability to move and operate freely. In order for the robots to perform to the expectations in manufacturing, their position and orientation must be determined accurately. In addition, there is a strong tendency to grant more autonomy to robots when they operate in hazardous or unknown e...

In this paper, we present the work related to the application of a visual odometry approach to estimate the location of mobile robots operating in off-road conditions. The visual odometry approach is based on template matching, which deals with estimating the robot displacement through a matching process between two consecutive images. Standard visual odometry has been improved using visual com...

ArmAssist is a wireless robot for after stroke upper limb rehabilitation. In this paper, we describe a method based on artificial landmark navigation system. The navigation system is only based in three optical mouse sensors. This enables to build a cheap but reliable position sensor. Two of the sensors are the data source for odometry calculations, and the third optical mouse sensor takes very...