14 accepted papers
Achieving dexterous robotic grasping with multi-fingered hands remains a significant challenge. While existing methods rely on complete 3D scans to predict grasp poses, these approaches face limitations due to the difficulty of acquiring high-quality 3D data in real-world scenarios. In this paper, w
Shape completion networks have been used recently in real-world robotic experiments to complete the missing/hidden information in environments where objects are only observed in one or few instances where self-occlusions are bound to occur. Nowadays, most approaches rely on deep neural networks that
Real-world robotic grasping can be done robustly if a complete 3D Point Cloud Data (PCD) of an object is available. However, in practice, PCDs are often incomplete when objects are viewed from few and sparse viewpoints before the grasping action, leading to the generation of wrong or inaccurate gras…
Implicit communication plays such a crucial role during social exchanges that it must be considered for a good experience in human-robot interaction. This work addresses implicit communication associated with the detection of physical properties, transport, and manipulation of objects. We propose an…
For collaborative tasks, involving handovers, humans are able to exploit visual, non-verbal cues, to infer physical object properties, like mass, to modulate their actions. In this paper, we investigate how the different levels of liquid inside a cup can be inferred from the observation of the movem…
Postural synergies are used in robotics to facilitate the control of dexterous artificial hands. This is achieved by learning a latent space (synergy space) from grasp postures and directly controlling the hand in this space. In this work, we propose the use of a non-linear conditional model for lea…
Human interaction involves very sophisticated non-verbal communication skills like understanding the goals and actions of others and coordinating our own actions accordingly. Neuroscience refers to this mechanism as motor resonance, in the sense that the perception of another persons actions and sen…
Soft robotics is a thriving branch of robotics which takes inspiration from nature and uses affordable flexible materials to design adaptable non-rigid robots. However, their flexible behavior makes these robots hard to model, which is essential for a precise actuation and for optimal control. For s…
A defining characteristic of intelligent systems is the ability to make action decisions based on the anticipated outcomes. Video prediction systems have been demonstrated as a solution for predicting how the future will unfold visually, and thus, many models have been proposed that are capable of p…
Humans have the fascinating capacity of processing nonverbal visual cues to understand and anticipate the actions of other humans. This “intention reading” ability is underpinned by shared motor repertoires and action models, which we use to interpret the intentions of others as if they were our own
Close human-robot cooperation is a key enabler for new developments in advanced manufacturing and assistive applications. Close cooperation require robots that can predict human actions and intent, understanding human non-verbal cues. Recent approaches based on neural networks have led to encouragin…
The detection of small forces is of great interest in any robotic application that involves interaction with the environment (e.g., objects manipulation, physical human-robot interaction, minimally invasive surgery), since it allows the robot to detect the contacts early on and to act accordingly. I
The letter reports an evaluation of the iCub grasping capabilities, performed using the YCB Object and Model Set. The goal is to understand what kind of objects the iCub dexterous hand can grasp, and with what degree of robustness and flexibility, given the best possible control strategy. Therefore,
The concept of affordances facilitates the encoding of relations between actions and effects in an environment centered around the agent. Such an interpretation has important impacts on several cognitive capabilities and manifestations of intelligence, such as prediction and planning. In this paper,