20 citations · 27 across the 11 of their papers we have counts for
11 papers
Real-Time Frame- and Event-based Object Detection with Spiking Neural Networks on Edge Neuromorphic Hardware: Design, Deployment and Benchmark
Udayanga G. W. K. N. Gamage, Yan Zeng, Cesar Cadena +2
Real-time object detection on energy-constrained platforms is critical for applications such as UAV-based inspection, autonomous navigation, and mobile robotics. Spiking neural net…
Learning-based Delay Compensation for Enhanced Control of Assistive Soft Robots
Adrià Mompó Alepuz, Dimitrios Papageorgiou, Silvia Tolu
Soft robots are increasingly used in healthcare, especially for assistive care, due to their inherent safety and adaptability. Controlling soft robots is challenging due to their n…
Event-based Civil Infrastructure Visual Defect Detection: ev-CIVIL Dataset and Benchmark
Udayanga G. W. K. N. Gamage, Xuanni Huo, Luca Zanatta +4
Small unmanned aerial vehicle (UAV)-based visual inspections are a more efficient alternative to manual methods for examining civil structural defects, offering safe access to haza…
Assisted Physical Interaction: Autonomous Aerial Robots with Neural Network Detection, Navigation, and Safety Layers
Andrea Berra, Viswa Narayanan Sankaranarayanan, Achilleas Santi Seisa +10
The paper introduces a novel framework for safe and autonomous aerial physical interaction in industrial settings. It comprises two main components: a neural network-based target d…
Adaptive Variable Impedance Control for a Modular Soft Robot Manipulator in Configuration Space
Mahmood Mazare, Silvia Tolu, Mostafa Taghizadeh
Compliance is a strong requirement for human-robot interactions. Soft-robots provide an opportunity to cover the lack of compliance in conventional actuation mechanisms, however, t…
RetinaNet Object Detector based on Analog-to-Spiking Neural Network Conversion
Joaquin Royo-Miquel, Silvia Tolu, Frederik E. T. Schöller +1
The paper proposes a method to convert a deep learning object detector into an equivalent spiking neural network. The aim is to provide a conversion framework that is not constrain…
2022 Roadmap on Neuromorphic Computing and Engineering
Dennis V. Christensen, Regina Dittmann, Bernabé Linares-Barranco +56
Modern computation based on the von Neumann architecture is today a mature cutting-edge science. In the Von Neumann architecture, processing and memory units are implemented as sep…
A Neurorobotic Embodiment for Exploring the Dynamical Interactions of a Spiking Cerebellar Model and a Robot Arm During Vision-based Manipulation Tasks
Omar Zahra, David Navarro-Alarcon, Silvia Tolu
While the original goal for developing robots is replacing humans in dangerous and tedious tasks, the final target shall be completely mimicking the human cognitive and motor behav…
Vision-Based Control for Robots by a Fully Spiking Neural System Relying on Cerebellar Predictive Learning
Omar Zahra, David Navarro-Alarcon, Silvia Tolu
The cerebellum plays a distinctive role within our motor control system to achieve fine and coordinated motions. While cerebellar lesions do not lead to a complete loss of motor fu…
Differential Mapping Spiking Neural Network for Sensor-Based Robot Control
Omar Zahra, Silvia Tolu, David Navarro-Alarcon
In this work, a spiking neural network (SNN) is proposed for approximating differential sensorimotor maps of robotic systems. The computed model is used as a local Jacobian-like pr…
Adaptive control for hindlimb locomotion in a simulated mouse through temporal cerebellar learning
T. P. Jensen, S. Tata, A. J. Ijspeert +1
Human beings and other vertebrates show remarkable performance and efficiency in locomotion, but the functioning of their biological control systems for locomotion is still only pa…