Energy management is essential for identifying potential savings and predicting the energy requirements of buildings. Energy meters are often located in underground spaces that are difficult to reach with wireless technology. This paper presents an experimental study comparing different Low Power Wide Area Networks (LPWAN) technologies in terms of building penetration and radio coverage. The technologies Low Power Long Range Wide Area Networks (LoRaWAN®), Narrow Band Internet of Things (NB-IoT), Sigfox 0G and Wireless Smart Ubiquitous Networks (Wi-SUN®) are evaluated experimentallyThis paper also proposes a distributed hybrid IoT system design that combines multiple LPWAN technologies using an abstraction layer to optimize cost and coverage. Communication is message-based using the publish-subscribe messaging pattern. It is implemented using the MQTT protocol. The abstraction layer decodes the proprietary binary data and converts it to a normalized JSON format.

Mobile manipulators extend the workspace of industrial manipulators by mounting them on mobile platforms. In this paper we present a trajectory control scheme for a special class of mobile manipulators. The mobile manipulator consists of a mobile platform driven by two Differential Drive Steering Units (DDSUs) and a robotic arm with 6 Degrees of Freedom (DoF). The mobile platform provides additional 3 DoF in motion. This results in a total of 9 DoF in the configuration space for the entire mobile manipulator. This paper develops a trajectory control scheme for mobile platforms driven by DDSUs that incorporates the kinematic motion constraints of the system. We propose a control and sensing scheme for high accuracy tracking relative to the workpiece. The proposed trajectory control scheme is evaluated by experimental analysis, which shows that the tracking control scheme can achieve end-effector mm accuracy relative to the workpiece.

Manipulators have been used in a large range of applications mainly in the production industry, but their application is limited in scenarios which need a very large working space. Mobile manipulators extend the workspace of manipulators by mounting them on mobile platforms. The paper presents the kinematic modeling and motion control for a special class of mobile manipulators. The mobile manipulator consists of a mobile platform driven by two Differential Drive Steering Units (DDSUs) and a robotic arm with 6 Degrees of Freedom (DoF). The mobile platform provides additional 3 DoF in motion. This leads to a total of 9 DoF in the configuration space for the whole mobile manipulator. The paper develops a generic kinematic model of mobile platforms driven by DDSUs that includes the kinematic motion constraints of the system. By allowing the concurrent use of all DoF in the configuration space, this enables large scale continuous manipulation task like performing welding operations exceeding the reach of commonly used manipulators. The developed kinematic model is evaluated by experimental analysis.

For a variety of applications, the task of global localization is to determine both, the position and the orientation of one or more mobile objects. An important area of application is mobile robotics, where knowledge of the heading angle is of great importance. One way to localize a mobile robot in real time is to use a network consisting of IEEE 802.15.4a radio nodes based on Ultra-wideband (UWB) technology. In addition to measuring the signal propagation time, UWB radio nodes equipped with multiple transceiver modules can also estimate the Angle of Arrival (AoA) of the signal by capturing the phase differences. The additional angle information can be used to increase location accuracy and reduce the absolute number of radio nodes required in a deployment environment. For this reason, this paper investigates the feasibility of AoA estimation based on UWB radio nodes. Specifically, radio nodes from Nanotron Technologies/Inpixon based on the swarm bee ER module are employed. One problem of the specific circuit board design used is that the antenna spacing is so large that ambiguities occur when detecting the phase differences, which leads to large AoA estimation errors. Hence, methods for solving this problem are presented and their functionality is evaluated based on real world measurements.

This paper presents a new approach for kinodynamic online motion planning for Automated Guided Vehicles (AGVs) in industrial environments. AGVs normally transport large and heavy transport units such as Euro-pallets or mesh pallets. Nowadays just-in-time inventory management and lean production requires the transport of small transportation units. Thus a flexible material flow is needed that can not be fulfilled by continuous material handling devices like belt or roll conveyors. Our approach uses small holonomic AGVs that are equipped with safety laser range finders for our semi autonomous motion and path planning system. This system plans trajectories with respect to the kinodynamic constraints of the AGVs and the environment. The operator retains as much control as necessary and the vehicle can react online on course deviations and unforeseen changes in the environment.

Pedestrian localization systems require the knowledge of a user's position for manifold applications in indoor and outdoor environments. For this purpose several methods can be used, such as a Global Navigation Satellite System (GNSS). Since GNSS are not available in indoor environments or deep street canyons other techniques have to be used. This could be a time based or signal strength based radio localization system. In this paper a Time Difference of Arrival (TDoA) system is used and combined with a low cost accelerometer and gyroscope. Since the localization device is free mountable at the user's body, the raw data of the gyroscope must be rotated in a global frame. Therefore the accelerometer is used to compute the rotation angles in relation to the earth's gravity. The data of the accelerometer is also used for a step detection and a step length estimation as well. To fuse the different measurements an Extended Kalman Filter (EKF) is employed. While the system is initialized the orientation of the user is not available. Therefore an initial phase is prepended where a reduced model is used. In this phase the orientation has to develop while the user is moving. The duration of the phase is dynamic, depending on the quality of the TDoA measurements. Once the initial phase is passed the complete model is used. To evaluate the introduced algorithm experimental results in different environments are presented.

Pedestrian localization systems require the knowledge of a users position for manifold applications in indoor and outdoor environments. For this purpose severel methods can be used, such as a Global Navigation Satellite System (GNSS) or Inertial Navigation Systems (INS). Since GNSS are not available in indoor environments or street canyons, in this paper a 802.15.4a network is used to estimate the pedestrian's position. The used network platform provides the Time Difference of Arrival (TDoA) as well as the Received Signal Strength (RSS). To fuse both measurement types a novel method is implemented which is based on the Extended Kalman Filter (EKF). Due to the low accuracy of RSS it is ignored if the TDoA system performs well. But if the TDoA measurements are affected by multipath propagation or other effects the RSS values are used to identify those situations and to correct the estimated position of the user. To evaluate the algorithm experimental results in two different environments are presented.

Just-in-time inventory management and short production cycles require flexible material flow as well as usage of small transportation units. These demands can be met by using small Automated Guided Vehicles (AGVs) which act as a swarm of mobile robots. The paper presents real-time communication and localization for a swarm of mobile robots which transport Euro-bins in a distribution center or warehouse. Localization is realized by trilateration using range measurements obtained from an IEEE 802.15.4a CSS network. The IEEE 802.15.4a network is used for communication as well as for localization. The paper presents the design of the networks as well as the communication protocol which provides communication and localization in real-time. In order to support a large number of robots, the whole working area is divided into cells which uses different frequencies. The network protocol provides handover between the cells and routing capabilities in real-time.

Automated Guided Vehicles (AGVs) are used in warehouses, distribution centers and manufacturing plants in order to automate the internal material flow. Usually AGVs are designed to transport large and heavy transport units such as Euro-pallets or mesh pallets. Just-in-time inventory management and lean production requires small transportation units to enable one-piece-flow. Furthermore short production cycles require a flexible material flow which can not be fulfilled by continuous material handling devices like belt or roll conveyors. A solution to meet these demands are small mobile robots for material transport which can replace conventional conveyor systems or large AGVs. The paper presents localization and tracking of an omnidirectional mobile robot equipped with Mecanum wheels, which was designed to transport Euro-bins in a distribution center or warehouse. Localization is realized by sensor fusion of range measurements obtained from an IEEE 802.15.4a network and laser range finders. The IEEE 802.15.4a network is used for communication as well as for global localization. Laser range finders are used to detect landmarks and to provide accurate positioning for docking maneuvers. The range measurements are fused in a Monte Carlo Particle Filter. The paper develops a new motion model for an omnidirectional robot as well as a sensor model for IEEE 802.15.4a range measurements. The experimental results presented in the paper show the effectiveness of the developed models.

Indoor location tracking of mobile robots or transport vehicles using wireless technology is attractive for many applications. IEEE 802.15.4a wireless networks offer an inexpensive facility for localizing mobile devices by time-based range measurements. The main problems of time-based range measurements in indoor environments are errors by multipath and non-line-of-sight (NLOS) signal propagation. This paper describes indoor tracking using range measurements and an Extended Kalman Filter with NLOS mitigation. The commercially available nanoLOC wireless network is utilized for range measurements. The paper presents experimental results of tracking a forklift truck in an industrial environment.

A wireless sensor network consist of spatially distributed autonomous sensor nodes for data acquisition. Accurate localization of sensor nodes is a strong requirement in a wide area of applications. This paper describes the localization of sensor nodes using range measurements and trilateration with the Extended Kalman Filter. The commercially available nanoLOC sensor network is utilized for range measurements. Experimental results show, that a localization accuracy better than 0.5 m can be achieved in most cases.

A warehouse management system is a key part of the supply chain and controls the movement of goods within a warehouse. Usually the state of a warehouse is managed in a central database, which must be updated for every storage and retrieval activity. The entire process is prone to errors, because it relies on manual activities performed by employees. This paper presents a technique to monitor the manual transportation processes of goods in a warehouse, in order to update the database automatically. In the proposed scenario, transport vehicles such as forklift trucks or pallet jacks are equipped with wireless sensor nodes and every storage and retrieval activity is reported to the warehouse management system. Tracking of transport vehicles is performed with nanoLOC sensor nodes, which offer range measurement capabilities. This radio positioning system determines the range between two devices by measuring the signal propagation delay. The paper describes the tracking of transport vehicles with range measurements and trilateration using the Extended Kalman Filter. It presents experimental results of tracking a forklift truck in a warehouse.