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Regulating contact forces with high precision is crucial for grasping and manipulating fragile or deformable objects. We aim to utilize the dexterity of human hands to regulate the contact forces for robotic hands and exploit human…
Drag-based image editing using generative models provides intuitive control over image structures. However, existing methods rely heavily on manually provided masks and textual prompts to preserve semantic fidelity and motion precision.…
The integration of advanced control strategies into prosthetic hands is essential to improve their adaptability and performance. In this study, we present an implementation of a Model Predictive Control (MPC) strategy to regulate the…
Embodied reference understanding is crucial for intelligent agents to predict referents based on human intention through gesture signals and language descriptions. This paper introduces the Attention-Dynamic DINO, a novel framework designed…
Precisely grasping an object is a challenging task due to pose uncertainties. Conventional methods have used cameras and fixtures to reduce object uncertainty. They are effective but require intensive preparation, such as designing jigs…
Parameter efficient transfer learning (PETL) is an emerging research spot that aims to adapt large-scale pre-trained models to downstream tasks. Recent advances have achieved great success in saving storage and computation costs. However,…
Diamagnetic levitation offers stable confinement of an object from its environment at zero power, and thus is a promising technique for developing next generation unclamped resonant sensors. In this work, we realize a resonant weighing…
Humans build 3D understandings of the world through active object exploration, using jointly their senses of vision and touch. However, in 3D shape reconstruction, most recent progress has relied on static datasets of limited sensory data…
Dexterous in-hand manipulation is an essential skill of production and life. However, the highly stiff and mutable nature of contacts limits real-time contact detection and inference, degrading the performance of model-based methods.…
A single nonholonomic under-actuated mobile robot with a bounded control range travels in a 3D workspace. This workspace also hosts a compact unknown domain with a smooth boundary. The robot has access to the horizontal distance to this…
In this work we show that macroscopic experiments can be used to investigate microscopic systems. Such macroscopic experiments enable testing the assumptions and results obtained by theoretical considerations or simulations that can not be…
We present RealPen, an augmented stylus for capacitive tablet screens that recreates the physical sensation of writing on paper with a pencil, ball-point pen or marker pen. The aim is to create a more engaging experience when writing on…
Track systems effectively distribute loads, augmenting traction and maneuverability on unstable terrains, leveraging their expansive contact areas. This tracked locomotion capability also aids in hand manipulation of not only regular…
This article extends the capabilities of the harmonic potential field approach to planning to cover both the kinematic and dynamic aspects of a robot motion. The suggested approach converts the gradient guidance field from a harmonic…
This paper introduces Dynamic Embeddings with Task-Oriented prompting (DETOT), a novel approach aimed at improving the adaptability and efficiency of machine learning models by implementing a flexible embedding layer. Unlike traditional…
For robot manipulation, a complete and accurate object shape is desirable. Here, we present a method that combines visual and haptic reconstruction in a closed-loop pipeline. From an initial viewpoint, the object shape is reconstructed…
A real-time motion training system for skydiving is proposed. Aerial maneuvers are performed by changing the body posture and thus deflecting the surrounding airflow. The natural learning process is extremely slow due to unfamiliar…
Digital sculpting is a popular means to create 3D models but remains a challenging task for many users. This can be alleviated by recent advances in data-driven and procedural modeling, albeit bounded by the underlying data and procedures.…
Different manipulation tasks require different types of grasps. For example, holding a heavy tool like a hammer requires a multi-fingered power grasp offering stability, while holding a pen to write requires a multi-fingered precision grasp…
Model-based manipulation of deformable objects has traditionally dealt with objects while neglecting their dynamics, thus mostly focusing on very lightweight objects at steady state. At the same time, soft robotic research has made…