Local reference filter for life-long vision aided inertial navigation

Filter based system state estimation is widely used for hard-realtime applications. In long-term filter operation the estimation of unobservable system states can lead to numerical instability due to unbounded state uncertainties. We introduce a filter concept that estimates system states in respect to changing local references instead of one global reference. In this way unbounded state covariances can be reset in a consistent way. We show how local reference (LR) filtering can be integrated into filter prediction to be used in square root filter implementations. The concept of LR-filtering is applied to the problem of vision aided inertial navigation (LR-INS). The results of a simulated 24 h quadrotor flight using the LR-INS demonstrate longterm filter stability. Real quadrotor flight experiments show the usability of the LR-INS for a highly dynamic system with limited computational resources

Computer-Controlled Test System for the Excitation of Very High-Order Modes in Highly Oversized Waveguides

The generation of a specific high-order mode with excellent mode purity in a highly oversized cylindrical waveguide is mandatorily required for the verification of high-power components at sub-THz frequencies. An example is the verification of quasi-optical mode conversion and output systems for fusion gyrotrons. A rotating high-order mode can be excited by taking a low-power RF source (e.g. RF network analyser) and by injecting the RF power via a horn antenna into a specific adjustable quasi-optical setup, the so-called mode generator. The manual adjustment of the mode generator is typically very time-consuming. An automatized adjustment using intelligent algorithms can solve this problem. In the present work, the intelligent algorithms consist of five different mode evaluation techniques to determine the azimuthal and radial mode indices, the quality factor, the scalar mode content and the amount of the counter-rotating mode. Here, the implemented algorithms, the design of the computer-controlled mechanical adjustment and test results are presented. The new system is benchmarked using an existing TE28,8 mode cavity operating at 140 GHz. In addition, the repeatability of the algorithms has been proven by measuring a newly designed TE28,10 mode generator cavity. Using the described advanced mode generator system, the quality of the excited modes has been significantly improved and the time for the proper adjustment has been reduced by at least a factor of 10

Designing Cathodes and Cathode Active Materials for Solid‐State Batteries

Solid-state batteries (SSBs) currently attract great attention as a potentially safe electrochemical high-energy storage concept. However, several issues still prevent SSBs from outperforming today\u27s lithium-ion batteries based on liquid electrolytes. One major challenge is related to the design of cathode active materials (CAMs) that are compatible with the superionic solid electrolytes (SEs) of interest. This perspective, gives a brief overview of the required properties and possible challenges for inorganic CAMs employed in SSBs, and describes state-of-the art solutions. In particular, the issue of tailoring CAMs is structured into challenges arising on the cathode-, particle-, and interface-level, related to microstructural, (chemo-)mechanical, and (electro-)chemical interplay of CAMs with SEs, and finally guidelines for future CAM development for SSBs are proposed

The LRU Rover for Autonomous Planetary Exploration and its Success in the SpaceBotCamp Challenge

The task of planetary exploration poses many challenges for a robot system, from weight and size constraints to sensors and actuators suitable for extraterrestrial environment conditions. As there is a significant communication delay to other planets, the efficient operation of a robot system requires a high level of autonomy. In this work, we present the Light Weight Rover Unit (LRU), a small and agile rover prototype that we designed for the challenges of planetary exploration. Its locomotion system with individually steered wheels allows for high maneuverability in rough terrain and the application of stereo cameras as its main sensor ensures the applicability to space missions. We implemented software components for self-localization in GPS-denied environments, environment mapping, object search and localization and for the autonomous pickup and assembly of objects with its arm. Additional high-level mission control components facilitate both autonomous behavior and remote monitoring of the system state over a delayed communication link. We successfully demonstrated the autonomous capabilities of our LRU at the SpaceBotCamp challenge, a national robotics contest with focus on autonomous planetary exploration. A robot had to autonomously explore a moon-like rough-terrain environment, locate and collect two objects and assemble them after transport to a third object - which the LRU did on its first try, in half of the time and fully autonomous

State Estimation for highly dynamic flying Systems using Key Frame Odometry with varying Time Delays

System state estimation is an essential part for robot navigation and control. A combination of Inertial Navigation Systems (INS) and further exteroceptive sensors such as cameras or laser scanners is widely used. On small robotic systems with limitations in payload, power consumption and computational resources the processing of exteroceptive sensor data often introduces time delays which have to be considered in the sensor data fusion process. These time delays are especially critical in the estimation of system velocity. In this paper we present a state estimation framework fusing an INS with time delayed, relative exteroceptive sensor measurements. We evaluate its performance for a highly dynamic flight system trajectory including a flip. The evolution of velocity and position errors for varying measurement frequencies from 15Hz to 1Hz and time delays up to 1s is shown in Monte Carlo simulations. The filter algorithm with key frame based odometry permits an optimal, local drift free navigation while still being computationally tractable on small onboard computers. Finally, we present the results of the algorithm applied to a real quadrotor by flying from inside a house out through the window

Toward a Fully Autonomous UAV: Research Platform for Indoor and Outdoor Urban Search and Rescue

Urban Search and Rescue missions raise special requirements on robotic systems. Small aerial systems provide essential support to human task forces in situation assessment and surveillance. As external infrastructure for navigation and communication is usually not available, robotic systems must be able to operate autonomously. Limited payload of small aerial systems poses a great challenge to the system design. The optimal tradeoff between flight performance, sensors and computing resources has to be found. Communication to external computers cannot be guaranteed, therefore all processing and decision making has to be done on-board. In this paper, we present a UAS system design fulfilling these requirements. The components of our system are structured into groups to encapsulate their functionality and interfaces.We use both laser and stereo vision odometry to enable seamless indoor and outdoor navigation. The odometry is fused with an Inertial Measurement Unit in an Extended Kalman Filter. Navigation is supported by a module that recognizes known objects in the environment. A distributed computation approach is adopted to address computational requirements of the used algorithms. The capabilities of the system are validated in flight experiments, using a quadrotor