Abstract A completely energy autarkic design for a classroom response system is presented. Maloperation by the user is prevented with the chosen design (no unnecessary buttons and switches). Electronic classroom response systems have been around for quite a while and do exist in various forms and flavors. Most commercially available solutions, however, have several disadvantages. The new device is an easy-to-use, robust form of a clicker, which takes its energy from the click itself, due to a very low-power system using only an energy of around 15 μ J per wireless telegram transmitted from each student to the teacher’s computer. The described system serves as both, a method to check students’ progress in any field of lecturing as well as a tool that (by its development) instructs students in the field of “Energy Harvesting for Small Wireless Devices”. The system also contributes to raising awareness of the material and energy balance in today’s electronics.

This paper summarizes an approach to segment 3D point clouds into drivable ground, obstacles, and overhangs. It was developed for outdoor Time-of-Flight cameras which only provide very sparse measurements. The proposed methodology takes advantage of the matrix-like data structure of the CMOS sensor for segmentation in order to increase efficiency. Furthermore, it was tailored to handle typical offhighway characteristics with different slopes and missing measurements and can be adapted to various mounting positions and vehicle properties. First, the algorithm processes the data column-wise using geometric relations. Afterward, the neighborhood of a measurement is considered to improve the initial classification. Finally, overhangs are separated.

This paper proposes a robust detection method of uncut crop edges which is used for automated guidance of a combine harvester. The utilized stereo vision system allows for real-time depth perception of the environment. A three-dimensional elevation map of the terrain is constructed by the point cloud acquired in this way. The heights of crop and harvested areas are estimated using Expectation Maximization and segmented using of the clustering results. In a row-wise processing step, each scan line of heights is cross-correlated with a model function to compute possible candidate points located at the very crop edge. Using robust linear regression, a linear crop edge model is calculated, modeling the spatial distribution of the candidate points. An overall crop edge model is updated via exponentially weighted moving average.

In this paper, the integration of OpenStreetMap (OSM) geodata to a robot system which focuses on autonomous off-highway driving is presented. It is shown, how the OSM data is enriched with other data sources and how the map information is processed to generate a path that fits to the capabilities of the robot. Based on the map information, the quality of Global Satellite Navigation System (GNSS) signals is estimated and incorporated into the routing process, e.g. to avoid path with a high probably of GNSS disturbances. Furthermore, it is demonstrated how the robot's localization based on a Carlson filter can be improved by these estimations.

In this paper, an obstacle detection system for field applications is presented which relies on the output of a stereo vision camera. In a first step, it splits the point cloud into cells which are analyzed in parallel. Here, features like density and distribution of the points and the normal of a fitted plane are taken into account. Finally, a neighborhood analysis clusters the obstacles and identifies additional ones based on the terrain slope. Furthermore, additional properties can be easily derived from the grid structure like a terrain traversability estimation or a dominant ground plane. The experimental validation has been done on a modified tractor on the field, with a test vehicle on the campus and within the forest.

Louis A. Masson , Stefano Rossi , Federico Belloni , Nickolay Mullin, Reto Wiesendanger, Markus Rothacher, Christine Hollenstein, Benjamin Männel, Daniel Willi, Michael Fisler, Patrick Fleischmann , Heinz Mathis , Martin Klaper, Marcel Joss, Erich Styger eSpace, EPFL, Station 13, 1015, Lausanne, Switzerland, ELSE SA, Chemin de la Raye 13, 1024 Ecublens, Switzerland (2) Institute of Geodesy and Photogrammtry, ETH Zürich, Robert-Gnehm-Weg 15, 8093 Zurich, Switzerland Institute for Communication Systems, HSR University of Applied Sciences of Eastern Switzerland, Oberseestrasse 10, 8640 Rapperswil, Switzerland, (4) Competence Center for Electronics, Lucerne University of Applied Sciences and Arts (HSLU), Technikumstrasse 21, CH-6048 Horw (Lucerne), Switzerland (5) Swiss Space Center, , EPFL, Station 13, 1015, Lausanne, Switzerland (6) Bauman Moscow State University, 2-ya Baumanskaya ul., 5, Moskva, Russia, 105005

The cross-correlation method allows phase-noise measurements of high-quality devices with very low noise levels, using reference sources with higher noise levels than the device under test. To implement this method, a phase-noise analyzer needs to compute the cross-spectral density, that is, the Fourier transform of the cross-correlation, of two time series over a wide frequency range, from fractions of Hz to tens of MHz. Furthermore, the analyzer requires a high dynamic range to accommodate the phase noise of high-quality oscillators that may fall off by more than 100 dB from close-in noise to the noise floor at large frequency offsets. This paper describes the efficient implementation of a cross-spectrum analyzer in a low-cost FPGA, as part of a modern phase-noise analyzer with very fast measurement time.

CubETH is a project to evaluate and demonstrate possibilities of low-cost GNSS receivers on a nano-satellite by following the Cubesat standard. The development of this new Swiss cubesat mission is underway at the Swiss Polytechnical Schools, launch is planned for 2016. Scientific goal are: precise orbit determination and estimate of satellite attitude based on a very short baseline together with a number of other experimental measurements. Programmatic goal is to implement this project in cooperation between federal (ETH/EPF domain) and cantonal (FH/HES domain) engineering schools and industrial partners. The educational objective is to involve engineering students from various schools across Switzerland to promote innovative teaching of engineering of complex systems. In this paper, we will discuss performance requirements for the CubETH spacecraft and its payload. We also show how lessons learned from the Swisscube satellite were used for the design and implementation of this project.

CubETH is a project to evaluate and demonstrate possibilities of low-cost GNSS receivers on a nano-satellite by following the Cubesat standard. The development of this new Swiss cubesat mission is underway at the Swiss Polytechnical Schools, launch is planned for 2016. Scientific goal are: precise orbit determination and estimate of satellite attitude based on a very short baseline together with a number of other experimental measurements. Programmatic goal is to implement this project in cooperation between federal (ETH/EPF domain) and cantonal (FH/HES domain) engineering schools and industrial partners. The educational objective is to involve engineering students from various schools across Switzerland to promote innovative teaching of engineering of complex systems. In this paper, we will discuss performance requirements for the CubETH spacecraft and its payload. We also show how lessons learned from the Swisscube satellite were used for the design and implementation of this project.

This paper addresses a planning approach based on B-splines for successively generated trajectories. Additionally, the lateral controller which was used to calculate the steering angle is described and the method how the required parameters were determined is introduced. It is explained how the output of a perception system is used to generate control points for the trajectory and how the inputs of the path tracker are derived from the B-splines which are represented as Bézier curves. The performance of the planning and control approach was tested on two different agricultural machines and also within a windrow guidance application.

This paper presents a B-spline based path planning approach for agricultural guidance applications which is able to handle successively generated trajectories. Additionally, the lateral controller which was used to calculate the steering angle is described and the method by which the required parameters were determined is introduced. We explain stepwise how the output of a perception system is used to determine the control points for the planner and why B-splines and Bezier curves are used to model the trajectory. Moreover, it is shown how the inputs for the path tracker are derived from the B-splines. The approach was implemented on two different farm machines where the performance of the planning and control approach were evaluated. Furthermore, both algorithms were used to build a windrow guidance demonstrator.

Robotic software frameworks have critical impact on development effort and quality of robot control systems. This paper provides a condensed overview on the complex topic of robotic framework design. Important areas of design are discussed - together with design principles applied in state-of-the-art solutions. They are related to software quality attributes with a brief discussion on their impact. Based on this analysis, the approaches taken in the framework FINROC are briefly presented.

This paper proposes a new algorithm called soft partitioning particle swarm optimization (SPPSO), which performs video-based markerless human pose tracking by optimizing a fitness function in a 31-dimensional search space. The fitness function is based on foreground segmentation and edges. SPPSO divides the optimization into two stages that exploit the hierarchical structure of the model. The first stage only optimizes the most important parameters, whereas the second is a global optimization which also refines the estimates from the first stage. Experiments with the publicly available Lee walk dataset showed that SPPSO performs better than the annealed particle filter at a frame rate of 20 fps, and equally well at 60 fps. The better performance at the lower frame rate is attributed to the explicit exploitation of the hierarchical model structure.