Related papers: A Universal Flexible Neuromorphic Tactile System w…
Beyond providing accurate movements, achieving smooth motion trajectories is a long-standing goal of robotics control theory for arms aiming to replicate natural human movements. Drawing inspiration from biological agents, whose reaching…
The term ``neuromorphic'' refers to systems that are closely resembling the architecture and/or the dynamics of biological neural networks. Typical examples are novel computer chips designed to mimic the architecture of a biological brain,…
Neuromorphic vision, inspired by biological neural systems, has recently gained significant attention for its potential in enhancing robotic autonomy. This paper presents a systematic exploration of a proposed Neuromorphic Navigation…
Recent advancements in soft robots, human-machine interfaces, and wearable electronics have led to an increased demand for high-performance soft tactile sensors. Tomographic tactile sensor based on resistive coupling is a novel contact…
We present an approach to constructing a neuromorphic device that responds to language input by producing neuron spikes in proportion to the strength of the appropriate positive or negative emotional response. Specifically, we perform a…
This paper explores active sensing strategies that employ vision-based tactile sensors for robotic perception and classification of fabric textures. We formalize the active sampling problem in the context of tactile fabric recognition and…
Random device mismatch that arises as a result of scaling of the CMOS (complementary metal-oxide semi-conductor) technology into the deep submicron regime degrades the accuracy of analogue circuits. Methods to combat this increase the…
Neuromorphic engineering combines the architectural and computational principles of systems neuroscience with semiconductor electronics, with the aim of building efficient and compact devices that mimic the synaptic and neural machinery of…
Stable and robust robotic grasping is essential for current and future robot applications. In recent works, the use of large datasets and supervised learning has enhanced speed and precision in antipodal grasping. However, these methods…
EMG-based gesture recognition shows promise for human-machine interaction. Systems are often afflicted by signal and electrode variability which degrades performance over time. We present an end-to-end system combating this variability…
Recent animal studies have shown that biological brains can enter a low power mode in times of food scarcity. This paper explores the possibility of applying similar mechanisms to a broad class of neuromorphic systems where power…
Neuromorphic devices represent an attempt to mimic aspects of the brain's architecture and dynamics with the aim of replicating its hallmark functional capabilities in terms of computational power, robust learning and energy efficiency. We…
Tactile sensing in biological organisms is deeply intertwined with morphological form, such as human fingers, cat paws, and elephant trunks, which enables rich and adaptive interactions through a variety of geometrically complex structures.…
Analog neuromorphic photonic processors are uniquely positioned to harness the ultrafast bandwidth and inherent parallelism of light, enabling scalability, on-chip integration and significant improvement in computational performance.…
To ensure that a robot is able to accomplish an extensive range of tasks, it is necessary to achieve a flexible combination of multiple behaviors. This is because the design of task motions suited to each situation would become increasingly…
Neuromorphic vision made significant progress in recent years, thanks to the natural match between spiking neural networks and event data in terms of biological inspiration, energy savings, latency and memory use for dynamic visual data…
The most common sensing modalities found in a robot perception system are vision and touch, which together can provide global and highly localized data for manipulation. However, these sensing modalities often fail to adequately capture the…
The development of tactile sensing is expected to enhance robotic systems in handling complex objects like deformables or reflective materials. However, readily available industrial grippers generally lack tactile feedback, which has led…
Achieving personalized intelligence at the edge with real-time learning capabilities holds enormous promise in enhancing our daily experiences and helping decision making, planning, and sensing. However, efficient and reliable edge learning…
The ever-increasing demand for Artificial Intelligence (AI) systems is underlining a significant requirement for new, AI-optimised hardware. Neuromorphic (brain-like) processors are one highly-promising solution, with photonic-enabled…