Related papers: Digger Finger: GelSight Tactile Sensor for Object …

Real-world robots localize objects from natural-language instructions while scenes around them keep changing. Yet most of the existing 3D visual grounding (3DVG) method still assumes a reconstructed and up-to-date point cloud, an assumption…

Dexterous manipulation has broad applications in assembly lines, warehouses and agriculture. To perform large-scale manipulation tasks for various objects, a multi-fingered robotic hand sometimes has to sequentially adjust its grasping…

Soft robots are powerful tools for manipulating delicate objects, yet their adoption is hindered by two gaps: the lack of integrated tactile sensing and sensor signal distortion caused by actuator deformations. This paper addresses these…

To enhance robotic grasping capabilities, we are developing new contactless fingertip sensors to measure distance in close proximity and simultaneously detect the type of material and the interior structure. These sensors are referred to as…

The convergence of the physical and digital realms has ushered in a new era of immersive experiences and seamless interactions. As the boundaries between the real world and virtual environments blur and result in a "mixed reality," there…

Detecting objects of interest, such as human survivors, safety equipment, and structure access points, is critical to any search-and-rescue operation. Robots deployed for such time-sensitive efforts rely on their onboard sensors to perform…

Ground Penetrating Radar (GPR) is one of the most important non-destructive evaluation (NDE) devices to detect subsurface objects (i.e., rebars, utility pipes) and reveal the underground scene. The two biggest challenges in GPR-based…

Tactile sensing has recently been used in robotics for object identification, grasping, and material recognition. Most material recognition approaches use vibration information from a tactile exploration, typically above one second long, to…

Vision-based tactile sensors use structured light to measure deformation in their elastomeric interface. Until now, vision-based tactile sensors such as DIGIT and GelSight have been using a single, static pattern of structured light tuned…

Tactile perception is crucial for a variety of robot tasks including grasping and in-hand manipulation. New advances in flexible, event-driven, electronic skins may soon endow robots with touch perception capabilities similar to humans.…

Grasping in dense clutter is a fundamental skill for autonomous robots. However, the crowdedness and occlusions in the cluttered scenario cause significant difficulties to generate valid grasp poses without collisions, which results in low…

One goal of dexterous robotic grasping is to allow robots to handle objects with the same level of flexibility and adaptability as humans. However, it remains a challenging task to generate an optimal grasping strategy for dexterous hands,…

We present the design, implementation, and evaluation of RF-Grasp, a robotic system that can grasp fully-occluded objects in unknown and unstructured environments. Unlike prior systems that are constrained by the line-of-sight perception of…

In open-pit mining, holes are drilled into the surface of the excavation site and detonated with explosives to facilitate digging. These blast holes need to be inspected internally to assess subsurface material types and drill quality, in…

Gaussian splatting has emerged as a powerful tool for high-fidelity reconstruction of dynamic scenes. However, existing methods primarily rely on implicit motion representations, such as encoding motions into neural networks or per-Gaussian…

The ability to grasp and manipulate transparent objects is a major challenge for robots. Existing depth cameras have difficulty detecting, localizing, and inferring the geometry of such objects. We propose using neural radiance fields…

Simulating vision-based tactile sensors enables learning models for contact-rich tasks when collecting real world data at scale can be prohibitive. However, modeling the optical response of the gel deformation as well as incorporating the…

Grasping objects with diverse mechanical properties, such as heavy, slippery, or fragile items, remains a significant challenge in robotics. Conventional grippers often rely on applying high normal forces, which can cause damage to objects.…

Soft grippers are gaining significant attention in the manipulation of elastic objects, where it is required to handle soft and unstructured objects which are vulnerable to deformations. A crucial problem is to estimate the physical…

Tactile sensing has proven to be an invaluable tool for enhancing robotic perception, particularly in scenarios where visual data is limited or unavailable. However, traditional methods for pose estimation using tactile data often rely on…