Fulvio Forni

Virtual model control (VMC) provides compliant trajectory execution, but sustained contact loads can produce residual positional error. This study evaluated the sequential development of VMC augmented with integral control for powered dry-bone resection and assessed the effects of end-effector stabilisation, spatial calibration and operating parameters. A seven-degree-of-freedom Franka Research 3 robot was commanded using VMC with integral control and carried a 4-mm diamond-tipped arthroscopic burr through a programmed 10 × 10 mm serpentine trajectory in 20 pounds-per-cubic-foot synthetic bone. Four sequential configurations were assessed: an original handle-based mount, an anthropomorphically designed shaft-stabilising mount, robot-frame calibration and workpiece registration. Each configuration comprised three resections. Performance was graded by one non-blinded assessor using a study-specific twelve-point score across burr-tip oscillation and X-, Y- and Z-axis deviation, with lower scores indicating better performance. Radial depth of cut, engagement depth, trajectory velocity and burr angle were then screened to identify candidate operating parameters. Mean total score decreased sequentially from 11.7/12 with the original mount to 7.7/12 after shaft stabilisation, 5.7/12 after robot-frame calibration and 4.0/12 after workpiece registration. The lowest observed score was maintained at an RDOC between 0.10 and 0.25 mm, a measured depth between 1.52 and 1.89 mm, velocity between 1.5 and 2.5 mm/s and a burr angle between 30 and 45 degrees. Mechanical stabilisation and spatial calibration were associated with progressively better resection performance using VMC with integral control. This exploratory benchtop study identified candidate operating ranges for further assessment in higher-fidelity models.

This paper introduces the ‘rebound winner-take-all (RWTA)’ motif as the basic element of a scalable neuromorphic control architecture. From the cellular level to the system level, the resulting architecture combines the reliability of discrete computation and the tunability of continuous regulation: it inherits the discrete computation capabilities of WTA state machines and the continuous tuning capabilities of excitable biophysical circuits. The proposed event-based framework addresses continuous rhythmic generation and discrete decision-making in a unified physical modeling language. We illustrate the versatility, robustness, and modularity of the architecture through the nervous system design of a snake robot.

We present a decentralized, agent agnostic, and safety-aware control framework for human-robot collaboration based on Virtual Model Control (VMC). In our approach, both humans and robots are embedded in the same virtual-component-shaped workspace, where motion is the result of the interaction with virtual springs and dampers rather than explicit trajectory planning. A decentralized, force-based stall detector identifies deadlocks, which are resolved through negotiation. This reduces the probability of robots getting stuck in the block placement task from up to 61.2% to zero in our experiments. The framework scales without structural changes thanks to the distributed implementation: in experiments we demonstrate safe collaboration with up to two robots and two humans, and in simulation up to four robots, maintaining inter-agent separation at around 20 cm. Results show that the method shapes robot behavior intuitively by adjusting control parameters and achieves deadlock-free operation across team sizes in all tested scenarios.

Robotic assistance allows surgeries to be reliably and accurately executed while still under the direct supervision of the surgeon, combining the strengths of robotic technology with the surgeon’s expertise. This article describes a robotic system designed to assist in surgical procedures by implementing a virtual drill guide. The system integrates virtual-fixture functionality using a novel virtual-mechanism controller with additional visual feedback. The controller constrains the tool to the desired axis, while allowing axial motion to remain under the surgeon’s control. Compared to prior virtual-fixture approaches—which primarily perform pure energy-shaping and damping injection with linear springs and dampers–our controller uses a virtual prismatic joint to which the robot is constrained by nonlinear springs, allowing us to easily shape the dynamics of the system. We detail the calibration procedures required to achieve sufficient precision and describe the implementation of the controller. We apply this system to a veterinary procedure: drilling for transcondylar screw placement in dogs. The results of the trials on 3D-printed bone models demonstrate sufficient precision to perform the procedure and suggest improved angular accuracy and reduced exit translation errors compared to patient-specific guides (PSGs). Discussion and future improvements follow.

Passivity-based control is a cornerstone of control theory and an established design approach in robotics. Its strength is based on the passivity theorem, which provides a powerful interconnection framework for robotics. However, the design of passivity-based controllers and their optimal tuning remain challenging. We propose here an intuitive design approach for fully actuated robots, where the control action is determined by a ‘virtual-mechanism’ as in classical virtual model control. The result is a robot whose controlled behavior can be understood in terms of physics. We achieve optimal tuning by applying algorithmic differentiation to ODE simulations of the rigid body dynamics. Overall, this leads to a flexible design and optimization approach: stability is proven by passivity of the virtual mechanism, while performance is obtained by optimization using algorithmic differentiation.

A theorem is proved to verify incremental stability of a feedback system via a homotopy from a known incrementally stable system, making no assumptions on existence of an extended space, well-posedness or causality. A first corollary of that result is that incremental stability may be verified by separation of Scaled Relative Graphs, correcting two assumptions in [1, Theorem 2]. Necessity of this correction is demonstrated by example. A second corollary provides an incremental version of the classical IQC stability theorem. Finally it is shown how to relax assumptions of incremental boundeness on the operators.

This paper presents a new design framework for dynamic output-feedback controllers for Lur'e oscillation in a multiple-input multiple-output setting. We first revisit and extend dominant system theory to state-dependent rates, with the goal of deriving conditions based on linear matrix inequalities. Then, we introduce a separation principle for Lur'e oscillator design, which allows for the independent design of a state-feedback oscillator and an observer. Our proposed control synthesis is demonstrated through the rhythm synchronization in multi-agent systems, illustrating how networks of stable, heterogeneous linear agents can be driven into phase-locked rhythmic behavior.

We propose a new class of passive nonlinear finite impulse response operators. This class is constructed by the action of finite impulse response filters in a lifted space. This allows for efficient control synthesis through constrained optimization. Closed-loop performance is taken into account through least-squares fitting, based on the theory of virtual reference feedback tuning. Passivity is established through efficient linear constraints, based on sampling in the frequency domain. Because of passivity, this class of operators is particularly suited for the control of physical systems, such as electromechanical systems.