43 citations · 118 across the 15 of their papers we have counts for
15 papers
Embedding ISO 10218 Safety Compliance in Robots via Control Barrier Functions for Human-Robot Collaboration
Federico Parma, Cesare Tonola, Nicola Pedrocchi +1
Human-Robot Collaboration (HRC) requires strict adherence to safety standards, such as ISO 10218, to prevent harmful interactions. Standard Speed and Separation Monitoring (SSM) fi…
Gesture-Based Robot Control Integrating Mm-wave Radar and Behavior Trees
Yuqing Song, Cesare Tonola, Stefano Savazzi +3
As robots become increasingly prevalent in both homes and industrial settings, the demand for intuitive and efficient human-machine interaction continues to rise. Gesture recogniti…
Learning and planning for optimal synergistic human-robot coordination in manufacturing contexts
Samuele Sandrini, Marco Faroni, Nicola Pedrocchi
Collaborative robotics cells leverage heterogeneous agents to provide agile production solutions. Effective coordination is essential to prevent inefficiencies and risks for human…
Reactive and Safety-Aware Path Replanning for Collaborative Applications
Cesare Tonola, Marco Faroni, Saeed Abdolshah +4
This paper addresses motion replanning in human-robot collaborative scenarios, emphasizing reactivity and safety-compliant efficiency. While existing human-aware motion planners ar…
OpenMORE: an open-source tool for sampling-based path replanning in ROS
Cesare Tonola, Manuel Beschi, Marco Faroni +1
With the spread of robots in unstructured, dynamic environments, the topic of path replanning has gained importance in the robotics community. Although the number of replanning str…
Predicting human motion intention for pHRI assistive control
Paolo Franceschi, Fabio Bertini, Francesco Braghin +3
This work addresses human intention identification during physical Human-Robot Interaction (pHRI) tasks to include this information in an assistive controller. To this purpose, hum…
Modeling and analysis of pHRI with Differential Game Theory
Paolo Franceschi, Manuel Beschi, Nicola Pedrocchi +1
Applications involving humans and robots working together are spreading nowadays. Alongside, modeling and control techniques that allow physical Human-Robot Interaction (pHRI) are…
Spatio-Temporal Avoidance of Predicted Occupancy in Human-Robot Collaboration
Jared Flowers, Marco Faroni, Gloria Wiens +1
This paper addresses human-robot collaboration (HRC) challenges of integrating predictions of human activity to provide a proactive-n-reactive response capability for the robot. Pr…
Optimal task and motion planning and execution for human-robot multi-agent systems in dynamic environments
Marco Faroni, Alessandro Umbrico, Manuel Beschi +3
Combining symbolic and geometric reasoning in multi-agent systems is a challenging task that involves planning, scheduling, and synchronization problems. Existing works overlooked…
Hiding task-oriented programming complexity: an industrial case study
Enrico Villagrossi, Michele Delledonne, Marco Faroni +2
The ease of use of robot programming interfaces represents a barrier to robot adoption in several manufacturing sectors because of the need for more expertise from the end-users. C…
Co-manipulation of soft-materials estimating deformation from depth images
Giorgio Nicola, Enrico Villagrossi, Nicola Pedrocchi
Human-robot co-manipulation of soft materials, such as fabrics, composites, and sheets of paper/cardboard, is a challenging operation that presents several relevant industrial appl…
Learning Action Duration and Synergy in Task Planning for Human-Robot Collaboration
Samuele Sandrini, Marco Faroni, Nicola Pedrocchi
A good estimation of the actions' cost is key in task planning for human-robot collaboration. The duration of an action depends on agents' capabilities and the correlation between…
Safety-aware time-optimal motion planning with uncertain human state estimation
Marco Faroni, Manuel Beschi, Nicola Pedrocchi
Human awareness in robot motion planning is crucial for seamless interaction with humans. Many existing techniques slow down, stop, or change the robot's trajectory locally to avoi…
Adaptive Hybrid Local-Global Sampling for Fast Informed Sampling-Based Optimal Path Planning
Marco Faroni, Nicola Pedrocchi, Manuel Beschi
This paper improves the performance of RRT-like sampling-based path planners by combining admissible informed sampling and local sampling (i.e., sampling the neighborhood of th…
Anytime informed path re-planning and optimization for robots in changing environments
Cesare Tonola, Marco Faroni, Nicola Pedrocchi +1
In this paper, we propose a path re-planning algorithm that makes robots able to work in scenarios with moving obstacles. The algorithm switches between a set of pre-computed paths…