20 accepted papers
Estimating the stiffness of Deformable Linear Objects (DLOs) is crucial for robust manipulation. Inferring this hidden property depends heavily on the physical interaction strategy. Through a 1D CNN-based analysis of predefined probing modes, we first demonstrate that boundary constraints and grasp …
The automation of Deformable Linear Object (DLO) manipulation remains a key challenge in industrial production. While prior works demonstrated reliable wire terminal insertion using vision and tactile sensing, they typically assume a fixed connector pose. This paper presents a dual-arm robotic syste…
This paper develops algorithms for planning time-optimal pick-and-place trajectories for multiple cylindrical containers filled with liquid and simultaneously transported by a robot. The considered trajectories comprise 3D translations combined with a 1D rotation about the vertical direction, i.e. S
This paper develops algorithms for planning time-optimal pick-and-place trajectories for multiple cylindrical containers filled with liquid and simultaneously transported by a robot. The considered trajectories comprise 3D translations combined with a 1D rotation about the vertical direction, i.e. S…
Robotic agri-food manipulation remains challenging because food items vary substantially in geometry, compliance, mass distribution, and surface properties, while their fragile nature makes grasping sensitive to small pose errors. This work presents a compact simulation-based study of how grasp topo…
Reliable grasp point selection on deformable linear objects, such as cables, requires not only accurate depth estimation but also awareness of prediction reliability. We present a five-stage stereo network for joint disparity, semantic, and uncertainty estimation, and use the predicted uncertainty t…
The robotic manipulation of deformable objects, such as clothes and fabric, is known as a complex task from both the perception and planning perspectives. Indeed, the stochastic nature of the underlying environment dynamics makes it an interesting research field for statistical learning approaches a…
The perception of Deformable Linear Objects (DLOs) is a challenging task due to their complex and ambiguous appearance, lack of discernible features, typically small sizes, and deformability. Despite these challenges, achieving a robust and effective segmentation of DLOs is crucial to introduce robo
Manipulating Deformable Linear Objects (DLOs) is a challenging task for a robotic system due to their unpredictable configuration, high-dimensional state space and complex nonlinear dynamics. This paper presents a framework addressing the manipulation of DLOs, specifically targeting the model-based
Deformable Objects (DOs), e.g. clothes, garments, cables, wires, and ropes, are pervasive in our everyday environment. Despite their importance and widespread presence, many limitations exist when deploying robotic systems to interact with DOs. One source of challenges arises from their complex perc…
The presence of Deformable Linear Objects (DLOs) such as wires, cables or ropes in our everyday life is massive. However, the applicability of robotic solutions to DLOs is still marginal due to the many challenges involved in their perception. In this letter, a methodology to generate datasets from
This letter presents <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DLO3DS</i> , an approach for the 3D shapes estimation and tracking of Deformable Linear Objects (DLOs) such as cables, wires or plastic hoses, using a cheap and compact 2D vision se
Advanced Human-In-The-Loop (HITL) control strategies for robot hands based on surface electromyography (sEMG) are among major research questions in robotics. Due to intrinsic complexity and inaccuracy of labeling procedures, unsupervised regression of sEMG signals has been employed in literature, ho
In this paper, an approach for fast and accurate segmentation of Deformable Linear Objects (DLOs) named <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FASTDLO</i> is presented. A deep convolutional neural network is employed for background segmentat
One of the major challenges in robotics consists in developing successful control strategies for robotic grasping devices. In this scenario, one of the most interesting approaches regards the exploitation of surface electromyography(sEMG). In this work, we propose a novel sEMG-based <italic xmlns:mm
Nowadays, an increasingly diversification of products and production lines would largely benefit from intuitive and multimodal robot teaching strategies. The present article proposes an augmented kinesthetic teaching system, which is based on surface electromyographic (sEMG) measurements from the op
Replication of human hand motions on anthropomorphic robotic hands is typically treated in literature as the combination of two sub-problems: the measurement of human hand motions, and the mapping of such motions on the robotic hand. In this letter we focus on the second one. Different approaches ha
The scope of this letter is to show the applicability of the Twisted String Actuators (TSAs) for lightweight, wearable and assistive robotic applications. To this aim, we have developed a novel surface electromyography (sEMG)-driven soft ExoSuit using the TSAs to perform both single and dual-arm elb
In this letter we present a sEMG-driven human-in-the-loop (HITL) control designed to allow an assistive robot produce proper support forces for both muscular effort compensations, i.e. for assistance in physical tasks, and muscular effort generations, i.e. for the application in muscle strength trai
In this work, we deal with the problem of planning a manipulation task for a robotic system composed of at least one dexterous arm and a dexterous multi-fingered hand. The goal of the local planner is to include both, the arm and the hand, in the execution of the task in a coordinated way. This is a…