Search Results for author:
Found 21 papers, 7 papers with code
PointGrasp: Point Cloud-based Grasping for Tendon-driven Soft Robotic Glove Applications
The proposed pipeline demonstrates an average RMSE of 0. 8 $\pm$ 0. 39 cm for simple and 0. 11 $\pm$ 0. 06 cm for complex geometries.
Road Surface Defect Detection -- From Image-based to Non-image-based: A Survey
As a result, there has been a growing interest in the literature on the subject, leading to the development of various road surface defect detection methods.
Multi-class Road Defect Detection and Segmentation using Spatial and Channel-wise Attention for Autonomous Road Repairing
To demonstrate the effectiveness of our framework, we conducted various ablation studies and comparisons with prior methods on a newly collected dataset annotated with nine road defect classes.
Generating Future Observations to Estimate Grasp Success in Cluttered Environments
End-to-end self-supervised models have been proposed for estimating the success of future candidate grasps and video predictive models for generating future observations.
Inverse Image Frequency for Long-tailed Image Recognition
The long-tailed distribution is a common phenomenon in the real world.
Long-tailed Instance Segmentation using Gumbel Optimized Loss
Major advancements have been made in the field of object detection and segmentation recently.
Ranked #11 on
Instance Segmentation
on LVIS v1.0 val
Fast Composite Optimization and Statistical Recovery in Federated Learning
This paper investigates a class of composite optimization and statistical recovery problems in the FL setting, whose loss function consists of a data-dependent smooth loss and a non-smooth regularizer.
TC-SfM: Robust Track-Community-Based Structure-from-Motion
Specifically, a novel structure is proposed, namely, {\textit{track-community}}, in which each community consists of a group of tracks and represents a local segment in the scene.
Visual-Tactile Multimodality for Following Deformable Linear Objects Using Reinforcement Learning
It will be problematic to use a single sensory input to track the behaviour of such objects: vision can be subjected to occlusions, whereas tactile inputs cannot capture the global information that is useful for the task.
Multimodal perception for dexterous manipulation
Due to the complementary properties between visual and tactile senses, it is desirable for us to combine vision and touch for a synergistic perception and manipulation.
Logic Rules Meet Deep Learning: A Novel Approach for Ship Type Classification
The shipping industry is an important component of the global trade and economy, however in order to ensure law compliance and safety it needs to be monitored.
Representation and Processing of Instantaneous and Durative Temporal Phenomena
In this paper, we propose a new logic based temporal phenomena definition language, specifically tailored for Complex Event Processing, that allows the representation of both instantaneous and durative phenomena and the temporal relations between them.
Vision-Guided Active Tactile Perception for Crack Detection and Reconstruction
In recent years, computer vision techniques have been applied in detecting cracks in concrete structures.
Generation of GelSight Tactile Images for Sim2Real Learning
Preliminary experimental results have shown that the simulated sensor could generate realistic outputs similar to the ones captured by a real GelSight sensor.
Robotics
Spatio-temporal Attention Model for Tactile Texture Recognition
Recently, tactile sensing has attracted great interest in robotics, especially for facilitating exploration of unstructured environments and effective manipulation.
Surface Following using Deep Reinforcement Learning and a GelSightTactile Sensor
Tactile sensors can provide detailed contact in-formation that can facilitate robots to perform dexterous, in-hand manipulation tasks.
Robotics
GarmNet: Improving Global with Local Perception for Robotic Laundry Folding
Developing autonomous assistants to help with domestic tasks is a vital topic in robotics research.
Neural Logic Reinforcement Learning
Deep reinforcement learning (DRL) has achieved significant breakthroughs in various tasks.
ViTac: Feature Sharing between Vision and Tactile Sensing for Cloth Texture Recognition
In this paper, addressing for the first time (to the best of our knowledge) texture recognition from tactile images and vision, we propose a new fusion method named Deep Maximum Covariance Analysis (DMCA) to learn a joint latent space for sharing features through vision and tactile sensing.
Robotic Tactile Perception of Object Properties: A Review
Available tactile sensing technologies are briefly presented before an extensive review on tactile recognition of object properties.
