相关论文: SLURP! Spectroscopy of Liquids Using Robot Pre-Tou…

Computer vision seeks to infer a wide range of information about objects and events. However, vision systems based on conventional imaging are limited to extracting information only from the visible surfaces of scene objects. For instance,…

Robots benefit from being able to classify objects they interact with or manipulate based on their material properties. This capability ensures fine manipulation of complex objects through proper grasp pose and force selection. Prior work…

Recognizing an object's material can inform a robot on the object's fragility or appropriate use. To estimate an object's material during manipulation, many prior works have explored the use of haptic sensing. In this paper, we explore a…

Near Infrared (NIR) spectroscopy is widely used in industrial quality control and automation to test the purity and grade of items. In this research, we propose a novel sensorized end effector and acquisition strategy to capture spectral…

Liquids are an important part of many common manipulation tasks in human environments. If we wish to have robots that can accomplish these types of tasks, they must be able to interact with liquids in an intelligent manner. In this paper,…

Open containers, i.e., containers without covers, are an important and ubiquitous class of objects in human life. In this letter, we propose a novel method for robots to "imagine" the open containability affordance of a previously unseen…

This work explores the use of computer vision for image segmentation and classification of medical fluid samples in transparent containers (for example, tubes, syringes, infusion bags). Handling fluids such as infusion fluids, blood, and…

Material recognition can help inform robots about how to properly interact with and manipulate real-world objects. In this paper, we present a multimodal sensing technique, leveraging near-infrared spectroscopy and close-range high…

There is a growing interest in applying large language models (LLMs) in robotic tasks, due to their remarkable reasoning ability and extensive knowledge learned from vast training corpora. Grounding LLMs in the physical world remains an…

Solid particles, such as rice and coffee beans, are commonly stored in containers and are ubiquitous in our daily lives. Understanding those particles' properties could help us make later decisions or perform later manipulation tasks such…

Pouring a specific amount of liquid is a challenging task. In this paper we develop methods for robots to use visual feedback to perform closed-loop control for pouring liquids. We propose both a model-based and a model-free method…

We propose a deep visuo-tactile model for realtime estimation of the liquid inside a deformable container in a proprioceptive way.We fuse two sensory modalities, i.e., the raw visual inputs from the RGB camera and the tactile cues from our…

Liquids and granular media are pervasive throughout human environments, yet remain particularly challenging for robots to sense and manipulate precisely. In this work, we present a systematic approach at integrating capacitive sensing…

We present the first system to determine fluid properties using the LiDAR sensors present on modern smartphones. Traditional methods of measuring properties like viscosity require expensive laboratory equipment or a relatively large amount…

Hyperspectral imaging captures both spectral and spatial information from a sample. The near infrared (NIR, > 800 nm) is advantageous for biomedical imaging as it falls into the tissue transparency window but also contains vibrational…

Different types of liquids such as water, wine and medicine appear in all aspects of daily life. However, limited attention has been given to the task, hindering the ability of robots to avoid or interact with liquids safely. The…

Interpreting spectroscopy data is a critical bottleneck in automating chemical research and industrial characterization. Particularly within infrared (IR) spectroscopy, identifying compounds in complex, liquid-phase chemical mixtures…

Non-invasive detection of objects embedded inside an optically scattering medium is essential for numerous applications in engineering and sciences. However, in most applications light at visible or near-infrared wavebands is scattered by…

Neutrino experiments often use large volumes of water, organic scintillators or noble liquids as active detection material. Due to the large hydrostatic and buoyancy forces involved, precise knowledge of the liquid levels inside the…

Liquid perception is critical for robotic pouring tasks. It usually requires the robust visual detection of flowing liquid. However, while recent works have shown promising results in liquid perception, they typically require labeled data…