Asynchronous, event-driven sampling techniques adapt the sampling rate of sensory signals to their dynamics by effectively compressing the data with respect to synchronous, clock-driven sampling. In robotics, such techniques offer data and bandwidth reduction, together with high temporal resolution and low latency. Despite the fact that vision and auditory event-driven sensors are currently available, robots are still equipped with a plethora of other sensors that might benefit from the event-driven encoding. In this paper, we study five estimation algorithms that implement the event-driven encoding for off-the-shelf clock-driven sensors. Digital accelerometer datasets were used to validate the system in robotic applications; other datasets have been used to assess the general performance of the proposed approach. The two best algorithms in terms of six performance parameters have been implemented on a Xilinx Artix-7 FPGA platform, using 2892 LUTs and 3620 flip-flops and reducing the output bandwidth from -44% to -75%, over the considered datasets.


    Access

    Download


    Export, share and cite



    Title :

    Event-Driven Encoding Algorithms for Synchronous Front-End Sensors in Robotic Platforms



    Publication date :

    2019-01-01



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    006 / 629



    Robotic Platforms

    Aleo, I. / Arena, P. / De Fiore, S. et al. | Springer Verlag | 2013


    Benchmarking the Localization Accuracy of 2D SLAM Algorithms on Mobile Robotic Platforms

    Schmid, Matthias / Basu Thakur, Mugdha / Krovi, Venkat N | SAE Technical Papers | 2020


    Object Classification for Robotic Platforms

    Brandenburg, Samuel / Machado, Pedro / Shinde, Pranjali et al. | TIBKAT | 2020


    Event Driven Tactile Sensors for Artificial Devices

    ABOU KHALIL, ALI | BASE | 2020

    Free access

    FRUIT PICKING ROBOTIC INSTALLATION ON PLATFORMS

    MAOR YANIV | European Patent Office | 2023

    Free access