Visuo-haptic object perception for robots: an overview
N Navarro-Guerrero, S Toprak, J Josifovski… - Autonomous …, 2023 - Springer
The object perception capabilities of humans are impressive, and this becomes even more
evident when trying to develop solutions with a similar proficiency in autonomous robots …
evident when trying to develop solutions with a similar proficiency in autonomous robots …
Binding touch to everything: Learning unified multimodal tactile representations
The ability to associate touch with other modalities has huge implications for humans and
computational systems. However multimodal learning with touch remains challenging due to …
computational systems. However multimodal learning with touch remains challenging due to …
Touching a nerf: Leveraging neural radiance fields for tactile sensory data generation
Tactile perception is key for robotics applications such as manipulation. However, tactile
data collection is time-consuming, especially when compared to vision. This limits the use of …
data collection is time-consuming, especially when compared to vision. This limits the use of …
Skill generalization of tubular object manipulation with tactile sensing and sim2real learning
Tubular objects such as test tubes are common in chemistry and life sciences research
laboratories, and robots that can handle them have the potential to accelerate experiments …
laboratories, and robots that can handle them have the potential to accelerate experiments …
Unsupervised adversarial domain adaptation for sim-to-real transfer of tactile images
Transferring optical tactile skills learned from simulated environments to the real world
benefits many robotic tactile applications, which can reduce the cost of data collection …
benefits many robotic tactile applications, which can reduce the cost of data collection …
Beyond flat gelsight sensors: Simulation of optical tactile sensors of complex morphologies for sim2real learning
Recently, several morphologies, each with its advantages, have been proposed for the\textit
{GelSight} high-resolution tactile sensors. However, existing simulation methods are limited …
{GelSight} high-resolution tactile sensors. However, existing simulation methods are limited …
Marker or Markerless? Mode-Switchable Optical Tactile Sensing for Diverse Robot Tasks
Optical tactile sensors play a pivotal role in robot perception and manipulation tasks. The
membrane of these sensors can be painted with markers or remain markerless, enabling …
membrane of these sensors can be painted with markers or remain markerless, enabling …
SingleS2R: Single sample driven Sim-to-Real transfer for Multi-Source Visual-Tactile Information Understanding using multi-scale vision transformers
Due to variations in light transmission and wear on the contact head, existing visual-tactile
dataset building methods typically require a large amount of real-world data, making the …
dataset building methods typically require a large amount of real-world data, making the …
Bridging the simulation-to-real gap of depth images for deep reinforcement learning
While deep reinforcement learning (DRL) models are effective at learning appropriate
actions from high-dimensional data, they require large amounts of costly and time …
actions from high-dimensional data, they require large amounts of costly and time …
Marker-embedded tactile image generation via generative adversarial networks
Data-driven methods have been successfully applied to images from vision-based tactile
sensors to fulfill various manipulation tasks. Nevertheless, these methods remain inefficient …
sensors to fulfill various manipulation tasks. Nevertheless, these methods remain inefficient …