Achim Liers

ScatterWeb - Low Power Sensor Nodes and Energy Aware Routing

ScatterWeb, a distributed, heterogeneous platform for the ad-hoc deployment of sensor networks offers hardware together with open, fully documented software for the deployment of embedded sensor networks. Already low power by design, the sensor nodes offer additional energy conservation mechanisms and support energy efficient routing, such as, e.g., solar-aware routing. In order to enable a battery-free operation, the nodes implement permanent power sensing and start the transmission if and only if the energy stored in a capacitor is sufficient for the complete transmission plus the reception of an acknowledgement. Energy-aware routing takes the current incoming power of environmental energy sources into account. Depending on the current power generated by, e.g., solar cells, traffic is always forwarded by the nodes having sufficient power. Together with additional power saving, auto-configuration, and remote reprogramming techniques, these mechanisms enable ScatterWeb nodes to survive many years in real-life scenarios without any on-site maintenance.

ScatterWeb: A wireless sensornet platform for research and teaching

This article presents ScatterWeb, a distributed, heterogeneous platform for the ad-hoc deployment of sensor networks offering hardware and open, fully documented software for research and teaching in embedded sensor networks. ScatterWeb consists of sensor nodes and several gateways connecting the sensor network to other wired or wireless networks. Already low-power by design, the sensor nodes offer additional energy conservation mechanisms and support energy efficient routing and applications. Even image capturing and transmission is possible with a minimum of energy. Together with auto-configuration and remote reprogramming techniques, these power saving mechanisms enable ScatterWeb nodes to survive many years in real-life scenarios without any in-place maintenance.

FU-Fighters 2001 (Global Vision)

Our F180 team, the FU-Fighters, participated for the third time at the RoboCup competition. This year we used a heterogeneous team, consisting of improved differential drive robots and new omnidirectional robots. We designed new electronics and added prediction and path planning to the behavior control. Our team won fourth place in the SmallSize league competition.

Radio-based multi-sensor system for person tracking and indoor positioning

Sensor based person tracking is a challenging topic. The main objective is positioning in areas without GPS connection, i.e. indoors. A research project is carried out at BAM, Federal Institute for Materials Research and Testing, to develop and to validate a multi-sensor system for 3D localization. It combines body motion sensing and a guard system for the tracking and recording of the status of persons. The so named BodyGuard system was designed for sensor-based monitoring and radio-based transmission of the movement of a person. Algorithms were developed to transform the sensor data into a spatial coordinate. This paper describes how the BodyGuard system operates, which main components were used in the system, how the individual sensor data are converted into 3D motion data, with which algorithms the individual sensors are processed, how individual errors are compensated and how the sensor data are merged into a 3D Model. Final objective of the BodyGuard system is to determine the exact location of a person in a building, e.g. during fire-fighting operations.

Self-calibration-method for an inertial navigation system with three 3D sensors

Inertial Navigation Systems with three 3D sensors are used to localize moving persons. The accuracy of the localization depends on the quality of the sensor data of the multi-sensor system. In order to improve the accuracy, a self-calibration process based on the automatic 3D calibration was developed. Based on the calibration procedure of the accelerometer (ACC) and the magnetic field sensor (MAG), the additional integration of the gyroscope (GYRO) leads to a reduction of the indoor positioning error. This improves both the approximation for the accelerometer and the magnetic field sensor so that the standard deviation of a single sensor is minimized. A new calibration procedure of the gyroscope and the accuracy improvement of the localization of a moving person are presented.

Automatic 3D calibration for a multi-sensor system

A major current focus in multi-sensor systems for indoor localisation is how to calibrate the sensors. In this study, we introduce a new method for this task. By using the datafusion of the combined sensor data, we were able to eliminate the errors of an individual sensor. The challenging matter was the connection of the different sensors for a continuous calibration. The necessary data for the calibration were given due to the natural movement of a person. The examination of this values offers an automatic re-calibration without using a given calibration sequence. This finding is promising for improving the calculation of the exact position of a person, who is moving free in a room.

Application of the Inertial Navigation System 3D-Self-Calibration-Method for the Minimization of the Measurement Uncertainty

For the accuracy of inertial navigation systems for indoor localization it is important to get high quality sensor data of the multi-sensor system. This can be realized using high quality sensors or the developed 3D-self-calibration-method for low cost sensors. Based on the calibration procedure of the accelerometer (ACC) and the magnetic field sensor (MAG), the additional integration of the gyroscope (GYRO) leads to a reduction of the indoor positioning error. This improves both the approximation for the accelerometer, the magnetic field sensor and the gyroscope so that the standard deviation of a single sensor is minimized. There are errors in the whole system. To determine these error sources it is important to define the measurement uncertainty. In this paper it is presented that the measurement uncertainty can be reduced by the application of the developed 3D-self-calibration method.