10 accepted papers
Teleoperation presents a promising paradigm for remote control and robot proprioceptive data collection. Despite recent progress, current teleoperation systems still suffer from limitations in efficiency and ergonomics, particularly in challenging scenarios. In this paper, we propose CaFe-TeleVision…
Teleoperation presents a promising paradigm for remote control and robot proprioceptive data collection. Despite recent progress, current teleoperation systems still suffer from limitations in efficiency and ergonomics, particularly in challenging scenarios. In this paper, we propose CaFe-TeleVision
Leveraging the powerful reasoning capabilities of large language models (LLMs), recent LLM-based robot task planning methods yield promising results. However, they mainly focus on single or multiple homogeneous robots on simple tasks. Practically, complex long-horizon tasks always require collaborat
Open-world task planning, characterized by handling unstructured and dynamic environments, has been increasingly explored to integrate with long-horizon robotic manipulation tasks. However, existing evaluations of the capabilities of these planners primarily focus on single-arm systems in structured
Spectral super-resolution (SSR) from RGB images, which involves reconstructing hyperspectral images (HSIs) from color images, has recently received great attention. While convolutional neural network (CNN)-based methods have demonstrated strong performance, they often overlook the self-similarity ac…
A language can have different varieties. These varieties can affect the performance of natural language processing (NLP) models, including large language models (LLMs), which are often trained on data from widely spoken varieties. This paper introduces a novel and cost-effective approach to benchmar…
People tend to distribute information evenly in language production for better and clearer communication. In this study, we compared essays written by second language (L2) learners with various native language (L1) backgrounds to investigate how they distribute information in their non-native L2 pro…
Grasping is at the core of many robotic manipulation tasks. Despite the recent progress, closed-loop grasp planning in stacked scenes is still unsatisfactory, in terms of efficiency, stability, and most importantly, safety. In this letter, we present CSGP, a closed-loop safe grasp planning approach
Symmetry is ubiquitous in everyday objects. Humans tend to grasp objects by recognizing the symmetric regions. In this letter, we investigate how symmetry could boost robotic grasp detection. To this end, we present a learning-based method for detecting grasp from single-view RGB-D images. The key i
Reconstructing delicate geometric details with consumer RGB-D sensors is challenging due to sensor depth and poses uncertainties. To tackle this problem, we propose a unique geometry-guided fusion framework: 1) First, we characterize fusion correspondences with the geodesic curves derived from the m…