Automated Firmware Generation for Compressive Sensing on Heterogeneous Hardware.

In this paper, a model-based firmware generator is presented towards complex sampling schemes. The framework is capable of automatically generating a fixed-rate Shannon-compliant acquisition scheme, as well as a variable-rate compressive sensing acquisition scheme. The generation starts from a model definition, which consists of two main components, namely an acquisition sequence to implement and the platform on which the sequence should be implemented. This model is then combined with the specifications to be transformed into a functional firmware. When generating firmware for compressive sensing (CS) purposes, the defined acquisition sequence is automatically generated to implement a pseudo-random sampling scheme in agreement with the defined undersampling factor. The evaluation of the generated firmware is done by means of an example use-case, including a proposed strategy for synchronization between CS setups. This research attempts to reduce the development complexity for embedded CS to lower the threshold towards effective usage in the field.

Real-Time Sonar Fusion for Layered Navigation Controller.

Navigation in varied and dynamic indoor environments remains a complex task for autonomous mobile platforms. Especially when conditions worsen, typical sensor modalities may fail to operate optimally and subsequently provide inapt input for safe navigation control. In this study, we present an approach for the navigation of a dynamic indoor environment with a mobile platform with a single or several sonar sensors using a layered control system. These sensors can operate in conditions such as rain, fog, dust, or dirt. The different control layers, such as collision avoidance and corridor following behavior, are activated based on acoustic flow queues in the fusion of the sonar images. The novelty of this work is allowing these sensors to be freely positioned on the mobile platform and providing the framework for designing the optimal navigational outcome based on a zoning system around the mobile platform. Presented in this paper is the acoustic flow model used, as well as the design of the layered controller. Next to validation in simulation, an implementation is presented and validated in a real office environment using a real mobile platform with one, two, or three sonar sensors in real time with 2D navigation. Multiple sensor layouts were validated in both the simulation and real experiments to demonstrate that the modular approach for the controller and sensor fusion works optimally. The results of this work show stable and safe navigation of indoor environments with dynamic objects.

Low-cost synchronization of high-speed audio and video recordings in bio-acoustic experiments.

In this paper, we present a method for synchronizing high-speed audio and video recordings of bio-acoustic experiments. By embedding a random signal into the recorded video and audio data, robust synchronization of a diverse set of sensor streams can be performed without the need to keep detailed records. The synchronization can be performed using recording devices without dedicated synchronization inputs. We demonstrate the efficacy of the approach in two sets of experiments: behavioral experiments on different species of echolocating bats and the recordings of field crickets. We present the general operating principle of the synchronization method, discuss its synchronization strength and provide insights into how to construct such a device using off-the-shelf components.