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This work presents KMVO, a ground plane based visual odometry that utilizes the vehicle's kinematic model to improve accuracy and robustness. Instead of solving a generic image alignment problem, the motion parameters of a differential drive vehicle can be directly estimated from RGB- D image data. In addition, a method for outlier rejection is presented that can deal with large percentages of outliers...
Recent research deals more and more with the application of ultra high frequency (UHF) radio-frequency identification (RFID) on mobile robots. However, the sensing characteristics between the reader and the tag (i.e. detections and signal strength) are challenging to model due to the influence of environmental effects (e.g. tag density, reflection, diffraction, or absorption). In this paper, we address...
A map of occupied and free space in a robot's environment is a common prerequisite for navigational tasks. Although the first methods for occupancy mapping relied on a 2D grid representation, 3D volumetric approaches are becoming increasingly popular. In this paper we present a new volumetric mapping approach that is based on the OctoMap method. We designed this method to be more robust against measurement...
In this paper we propose a novel approach to classify detection events from a stream of radio-frequency identification (RFID) measurements for the purpose of mapping RFID transponders. Since raw readings from RFID readers only provide information on positive read attempts, i.e. the detections of a tag, we propose an outlier filter method solely based on the spatial extent of the sensor model that...
This work documents the implementation of a dynamic personality as a Human-Robot-Interface as well as the test of its effect. It creates an emergent personality structure for a robot based upon a psychological theory. The resulting emotions lead to different reactions and speech output of the robot. The personalities had a great impact on the user, the robot appeared more human-like and more emotional.
This paper addresses the task of calibrating the kinematic parameters and odometry of car-like robots with dual-axis steering. To achieve this goal only the robots builtin laser rangers and no external tracking systems are employed. We introduce a method to actively calibrate the steering angles of both front and rear steering angles with a multi-input multi-output (MIMO) controller. Using the determined...
We present a novel approach incorporating a combination of Radio-Frequency Identification (RFID) and odometry information into the motion control of a mobile robot for the purpose of path following in unknown environments. Our method utilizes RFID measurements as landmarks and makes the mobile robot autonomously follow a path that was previously recorded in a manual training phase. The approach needs...
A safe traversal of a mobile robot in an unknown environment requires the determination of local ground surface properties. As a first step, a broad structure of the underlying environment can be established by clustering terrain sections which exhibit similar features. In this work, we focus on an unsupervised learning approach to segment different terrain types according to the clustering of acquired...
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