arXiv subjects

Dario Onfiani

Publications and source records attributed to Dario Onfiani.

5 recordsLinked to original sources

arXiv2026

Receiver-Centered Robot-to-Human Handover with Grasp-Aware Object Orientation

Collaborative robots are increasingly sharing workspaces with human operators, making tool handover a frequent and safety-critical micro-interaction. However, traditional static handovers often lead to awkward grasps when handling asymmetric industrial tools. This paper presents a receiver-centered voice-driven adaptive handover system for mechanical tools, built on a Franka cobot. Using an LLM for intention recognition and MediaPipe for real-time 3D hand tracking, the framework dynamically adjusts the end-effector's orientation to present tools in an ergonomically optimal, handle-first pose. A within-subjects study compared this adaptive approach with an object-agnostic static baseline. The results demonstrate that the adaptive system reduces the grasp delay for asymmetric tools, improving the fluency of the interaction. Furthermore, the adaptive strategy improved specific trust-related perceptions, particularly motion predictability and perceived task simplicity.

cs.RO↗

arXiv2026

EMG-Based Adaptation of Anisotropic Virtual Fixtures for Robot-Assisted Surgical Resection and Dissection

In this paper, we address the development of an adaptive assistance system for robot-assisted laparoscopic surgery, specifically for delicate tasks such as Resection and Dissection. Even if Virtual Fixtures offer significant advantages for guiding a surgeon's movements, conventional Virtual Fixtures are often defined by fixed geometries, lacking the flexibility to adapt to the surgical workflow or the surgeon's immediate intent. To address these limitations, we propose a novel framework for an adaptive and anisotropic virtual fixture. In addition, we introduce an intuitive control interface that modulates the fixture's geometry in real-time based on the surgeon's intent, inferred from EMG signals. This approach allows the surgeon to dynamically expand or disengage the constraint by contracting their forearm muscles, enabling seamless transitions between precise guided motion and free repositioning of the tool. Experimental results from a pilot user study, based on a standardized surgical training task, demonstrate the effectiveness of the proposed method. The system showed significant improvements in task accuracy and movement consistency, alongside a reduction in perceived cognitive load, effort, and frustration.

cs.RO↗

arXiv2026

Adaptive vs. Static Robot-to-Human Handover: A Study on Orientation and Approach Direction

Robot-to-human handovers often rely on static, open-loop strategies (or, at best, approaches that adapt only the position), which generally do not consider how the object will be grasped by the human, thus requiring the user to adapt. This work presents a novel adaptive framework that dynamically adjusts the object's delivery pose in real time based on the user's hand pose and the intended downstream task. By integrating AI-based hand pose estimation with smooth, kinematically constrained trajectories, the system ensures a safe approach and an optimal handover orientation. A comprehensive user study compares the proposed adaptive approach against a static baseline across multiple tasks, evaluating both subjective metrics (NASA-TLX, Human-Robot Trust Scale) and objective physiological data (blink rate measured via wearable eye-trackers). The results demonstrate that dynamic alignment significantly reduces users' cognitive workload and physiological stress, while improving their confidence in the robot's reliability. These findings highlight the potential of task- and pose-aware systems for enabling fluid and ergonomic human-robot collaboration.

cs.RO↗

arXiv2025

Optimizing Design and Control Methods for Using Collaborative Robots in Upper-Limb Rehabilitation

In this paper, we address the development of a robotic rehabilitation system for the upper limbs based on collaborative end-effector solutions. The use of commercial collaborative robots offers significant advantages for this task, as they are optimized from an engineering perspective and ensure safe physical interaction with humans. However, they also come with noticeable drawbacks, such as the limited range of sizes available on the market and the standard control modes, which are primarily oriented towards industrial or service applications. To address these limitations, we propose an optimization-based design method to fully exploit the capability of the cobot in performing rehabilitation tasks. Additionally, we introduce a novel control architecture based on an admittance-type Virtual Fixture method, which constrains the motion of the robot along a prescribed path. This approach allows for an intuitive definition of the task to be performed via Programming by Demonstration and enables the system to operate both passively and actively. In passive mode, the system supports the patient during task execution with additional force, while in active mode, it opposes the motion with a braking force. Experimental results demonstrate the effectiveness of the proposed method.

cs.RO↗

arXiv2025

On the Analysis of Stability, Sensitivity and Transparency in Variable Admittance Control for pHRI Enhanced by Virtual Fixtures

The interest in Physical Human-Robot Interaction (pHRI) has significantly increased over the last two decades thanks to the availability of collaborative robots that guarantee user safety during force exchanges. For this reason, stability concerns have been addressed extensively in the literature while proposing new control schemes for pHRI applications. Because of the nonlinear nature of robots, stability analyses generally leverage passivity concepts. On the other hand, the proposed algorithms generally consider ideal models of robot manipulators. For this reason, the primary objective of this paper is to conduct a detailed analysis of the sources of instability for a class of pHRI control schemes, namely proxy-based constrained admittance controllers, by considering parasitic effects such as transmission elasticity, motor velocity saturation, and actuation delay. Next, a sensitivity analysis supported by experimental results is carried out, in order to identify how the control parameters affect the stability of the overall system. Finally, an adaptation technique for the proxy parameters is proposed with the goal of maximizing transparency in pHRI. The proposed adaptation method is validated through both simulations and experimental tests.

cs.RO↗