Development of a 2D Lidar SLAM algorithm for localization on the building construction site

In order to improve the autonomy of construction robots, a Simultaneous Localization and Mapping (SLAM) solution is needed that localizes the robot using solely on-board sensing with sub-5 mm accuracy. As pointed out by the results of the Hilti SLAM Challenge, the state-of-the-art in SLAM currently does not offer a solution that comes close to...

A Framework for Indoor Localization Using the Magnetic Field

In this work, our focus is on indoor localization using the indoor magnetic field as a source of position information. This relies on the fact that ferromagnetic materials inside buildings cause the magnetic field to vary spatially. We jointly estimate the pose of a combined sensor module (containing a magnetometer) as well as the magnetic field...

Indoor SLAM using a foot-mounted IMU and the local magnetic field

In this paper, a simultaneous localization and mapping algorithm for tracking the motion of a pedestrian with a foot-mounted inertial measurement unit is proposed. The algorithm uses two maps, namely, a motion map and a magnetic field map. The motion map captures typical motion patterns of pedestrians in buildings that are constrained by e.g....

ConvSequential-SLAM: A Sequence-Based, Training-Less Visual Place Recognition Technique for Changing Environments

Visual Place Recognition (VPR) is the ability to correctly recall a previously visited place under changing viewpoints and appearances. A large number of handcrafted and deep-learning-based VPR techniques exist, where the former suffer from appearance changes and the latter have significant computational needs. In this paper, we present a new...

Evaluating SLAM in an urban dynamic environment

Simultaneous Localization And Mapping (SLAM) algorithms provide accurate localization for autonomous vehicles and provide essential information for the path planning module. However, SLAM algorithms as- sume a static environment in order to estimate a location. This assumption influences the pose estimation in dynamic urban environments. The...

Design of a Hybrid-Range-LiDAR SLAM algorithm: a graph-based approach to SLAM using ultra-wideband radios

A fundamental prerequisite for many robot-tasks is the availability of an environment model. The ability of a robot to create such a model itself is crucial to having truly autonomous robots around in our daily lives. For basic robot-tasks, a two-dimensional grid-map that describes a distinction between inhabitable and uninhabitable space is a...

Local Accuracy in Global Uncertainty: The Design of a Particle Filter Based Hybrid Metric-Topological Mapping and Localization Framework

Mobile robots need to interact with their environment to perform their tasks. To be successful they often need to know what their surrounding looks like, and where they are located in that surrounding. The act of simultaneously estimating both the state of the robot and the state of the environment is called Simultaneous Localization And Mapping...

Gaining by forgetting: Towards long-term mobile robot autonomy in large scale environments using a novel hybrid metric-topological mapping system

The emerging of mobile robots in everyday life scenarios, such as in the case of domestic care robots, is highly anticipated. Much research has been carried out to make robots more capable of performing tasks in our everyday environments. Despite major progress over the last decades, many hurdles are still to be taken. In the field of robotic...