Neural states in parietal areas during arm reaching

Since the first subdivisions of the brain into macro regions, it has always been thought a priori that, given the heterogeneity of neurons, different areas host specific functions and process unique information in order to generate a behaviour. Moreover, the various sensory inputs coming from different sources (eye, skin, proprioception) flow from one macro area to another, being constantly computed and updated. Therefore, especially for non-contiguous cortical areas, it is not expected to find the same information. From this point of view, it would be inconceivable that the motor and the parietal cortices, diversified by the information encoded and by the anatomical position in the brain, could show very similar neural dynamics. With the present thesis, by analyzing the population activity of parietal areas V6A and PEc with machine learning methods, we argue that a simplified view of the brain organization do not reflect the actual neural processes. We reliably detected a number of neural states that were tightly linked to distinct periods of the task sequence, i.e. the planning and execution of movement and the holding of target as already observed in motor cortices. The states before and after the movement could be further segmented into two states related to different stages of movement planning and arm posture processing. Rather unexpectedly, we found that activity during the movement could be parsed into two states of equal duration temporally linked to the acceleration and deceleration phases of the arm. Our findings suggest that, at least during arm reaching in 3D space, the posterior parietal cortex (PPC) shows low-level population neural dynamics remarkably similar to those found in the motor cortices. In addition, the present findings suggest that computational processes in PPC could be better understood if studied using a dynamical system approach rather than studying a mosaic of single units.

A phase II, single arm study of CarbopLatin plus Etoposide with Bevacizumab and Atezolizumab in patients with exTEnded-disease small-cell lung cancer (SCLC) – CeLEBrATE trial

Small cell lung cancer (SCLC) is an aggressive neuroendocrine tumor diagnosed at extended disease SCLC (ES-SCLC) stage in about 70% of cases. The new standard of treatment for patients with ES-SCLC is a combination of platinum-etoposide chemotherapy and atezolizumab or durvalumab, two programmed cell death ligand 1 (PD-L1) inhibitory monoclonal antibodies (mAb). However, the benefit derived from the addition of PD-L1 inhibitors to chemotherapy in ES-SCLC was limited and restricted to a subset of patients. The vascular endothelial growth factor (VEGF) is the most important pro-angiogenic factor implicated in cancer angiogenesis, which is abundant in SCLC and associated with poor prognosis. Antiangiogenic agents, such as bevacizumab, a humanized mAb against VEGF, added to platinum-etoposide chemotherapy improved progression-free survival in SCLC in two trials, but it did not translate into a benefit in overall survival. Nevertheless, VEGF has also acts as a mediator of an immunosuppressive microenvironment and its inhibition can revert the immune-suppressive tumor microenvironment and potentially enhance the efficacy of immunotherapies. Based on available preclinical data, we hypothesized that VEGF inhibition by bevacizumab could improve atezolizumab efficacy in a synergistic way and designed a phase II single-arm trial of bevacizumab in combination with carboplatin, etoposide, and atezolizumab as first-line treatment in ES-SCLC. The trial, which is still ongoing, enrolled 53 patients, including those with treated or untreated asymptomatic brain metastases (provided criteria are met), who received atezolizumab, bevacizumab, carboplatin and etoposide for 4-6 cycles (induction phase), followed by maintenance with atezolizumab and bevacizumab for a maximum of 18 total cycles or until disease progression, patient refusal, unacceptable toxicity. The evaluation of efficacy of the experimental combination in terms of 1-year overall survival rate is not yet mature (primary objective of the trial). The combination was feasible and the toxicity profile manageable (secondary objective of the trial).

Relative influence of gaze and static arm position in the Superior Parietal Lobule of the macaque monkey during reaching

The superior parietal lobule (SPL) of macaques is classically described as an associative cortex implicated in visuospatial perception, planning and control of reaching and grasping movements (De Vitis et al., 2019; Galletti et al., 2003, 2018, 2022; Fattori et al., 2017; Hadjidimitrakis et al., 2015). These processes are the result of the integration of signals related to different sensory modalities. During a goal-directed action, eye and limb information are combined to ensure that the hand is transported at the gazed target location and the arm is maintained steady in the final position. The SPL areas V6A, PEc and PE contain cells sensitive to the direction of gaze and limb position but less is known about the degree of independent encoding of these signals. In this thesis, we evaluated the influence of eye and arm position information upon single neuron activity of areas V6A, PEc and PE during the holding period after the execution of arm reaching movement, when the gaze and hand are both still at the reach target. Two male macaques (Macaca fascicularis) performed a reaching task while single unit activity was recorded from areas V6A, PEc and PE. We found that neurons in all these areas were modulated by eye and static arm positions with a joint encoding of gaze and somatosensory signals in V6A and PEc and a mostly separate processing of the two signals in PE. The elaboration of this information reflects the functional gradient found in the SPL with the caudal sector characterized by visuo-somatic properties in comparison to the rostral sector dominated by somatosensory signals. This evidence well agree also with the recent reallocation of areas V6A and PEc in Brodmann’s area 7 depending on their similar structural and functional features with respect to PE belonging to Brodmann’s area 5 (Gamberini et al., 2020).

A robotic platform for precision agriculture and applications

Agricultural techniques have been improved over the centuries to match with the growing demand of an increase in global population. Farming applications are facing new challenges to satisfy global needs and the recent technology advancements in terms of robotic platforms can be exploited. As the orchard management is one of the most challenging applications because of its tree structure and the required interaction with the environment, it was targeted also by the University of Bologna research group to provide a customized solution addressing new concept for agricultural vehicles. The result of this research has blossomed into a new lightweight tracked vehicle capable of performing autonomous navigation both in the open-filed scenario and while travelling inside orchards for what has been called in-row navigation. The mechanical design concept, together with customized software implementation has been detailed to highlight the strengths of the platform and some further improvements envisioned to improve the overall performances. Static stability testing has proved that the vehicle can withstand steep slopes scenarios. Some improvements have also been investigated to refine the estimation of the slippage that occurs during turning maneuvers and that is typical of skid-steering tracked vehicles. The software architecture has been implemented using the Robot Operating System (ROS) framework, so to exploit community available packages related to common and basic functions, such as sensor interfaces, while allowing dedicated custom implementation of the navigation algorithm developed. Real-world testing inside the university’s experimental orchards have proven the robustness and stability of the solution with more than 800 hours of fieldwork. The vehicle has also enabled a wide range of autonomous tasks such as spraying, mowing, and on-the-field data collection capabilities. The latter can be exploited to automatically estimate relevant orchard properties such as fruit counting and sizing, canopy properties estimation, and autonomous fruit harvesting with post-harvesting estimations.

On the motion planning & control of nonlinear robotic systems

In the last decades, we saw a soaring interest in autonomous robots boosted not only by academia and industry, but also by the ever in- creasing demand from civil users. As a matter of fact, autonomous robots are fast spreading in all aspects of human life, we can see them clean houses, navigate through city traffic, or harvest fruits and vegetables. Almost all commercial drones already exhibit unprecedented and sophisticated skills which makes them suitable for these applications, such as obstacle avoidance, simultaneous localisation and mapping, path planning, visual-inertial odometry, and object tracking. The major limitations of such robotic platforms lie in the limited payload that can carry, in their costs, and in the limited autonomy due to finite battery capability. For this reason researchers start to develop new algorithms able to run even on resource constrained platforms both in terms of computation capabilities and limited types of endowed sensors, focusing especially on very cheap sensors and hardware. The possibility to use a limited number of sensors allowed to scale a lot the UAVs size, while the implementation of new efficient algorithms, performing the same task in lower time, allows for lower autonomy. However, the developed robots are not mature enough to completely operate autonomously without human supervision due to still too big dimensions (especially for aerial vehicles), which make these platforms unsafe for humans, and the high probability of numerical, and decision, errors that robots may make. In this perspective, this thesis aims to review and improve the current state-of-the-art solutions for autonomous navigation from a purely practical point of view. In particular, we deeply focused on the problems of robot control, trajectory planning, environments exploration, and obstacle avoidance.

Trajectory planning of single and dual-arm robots for time-optimal handling of liquids and objects

This Thesis studies the optimal control problem of single-arm and dual-arm serial robots to achieve the time-optimal handling of liquids and objects. The first topic deals with the planning of time-optimal anti-sloshing trajectories of an industrial robot carrying a cylindrical container filled with a liquid, considering 1-dimensional and 2-dimensional planar motions. A technique for the estimation of the sloshing height is presented, together with its extension to 3-dimensional motions. An experimental validation campaign is provided and discussed to assess the thoroughness of such a technique. As far as anti-sloshing trajectories are concerned, 2-dimensional paths are considered and, for each one of them, three constrained optimizations with different values of the sloshing-height thresholds are solved. Experimental results are presented to compare optimized and non-optimized motions. The second part focuses on the time-optimal trajectory planning for dual-arm object handling, employing two collaborative robots (cobots) and adopting an admittance-control strategy. The chosen manipulation approach, known as cooperative grasping, is based on unilateral contact between the cobots and the object, and it may lead to slipping during motion if an internal prestress along the contact-normal direction is not prescribed. Thus, a virtual penetration is considered, aimed at generating the necessary internal prestress. The stability of cooperative grasping is ensured as long as the exerted forces on the object remain inside the static-friction cone. Constrained-optimization problems are solved for 3-dimensional paths: the virtual penetration is chosen among the control inputs of the problem and friction-cone conditions are treated as inequality constraints. Also in this case experiments are presented in order to prove evidence of the firm handling of the object, even for fast motions.

Development of a robotic system for switchgear cabling

Industrial robots are an inalienable part of modern automated production. Typical applications of robots include welding, painting, (dis)assembly, packaging, labeling, palletizing, pick and place and others. Many of that applications includes object manipulation. If the shape and position of the object are known in advance, it is possible to design the trajectory of the robot’s end-effector to take and place. Such a strategy is applicable for rigid objects and widely used in the manufacturing field. But flexible (deformable) objects can change their shape and position upon contact with the robot’s end-effector or environment. That is the reason why the general approach is unacceptable. It means that the robot can fail to grasp such an object and can’t place it in the desired position. This thesis has addressed the problem of cable manipulation by bilateral robotic setup for the industrial manufacturing of electrical switchgear. The considered solution is based on the idea of tensioned cable. If the cable was grasped by the ends and tensioned, it has a line shape. Since the position of the robot’s end-effectors known, the position of the cable is known as well. Such an approach is capable to place cable in cable ducts of switchgear. The considered solution has been tested experimentally on a real bilateral robotic setup.

Integration of ROS for the control of industrial robotic systems in a proprietary environment

The paper deals with the integration of ROS, in the proprietary environment of the Marchesini Group company, for the control of industrial robotic systems. The basic tools of this open-source software are deeply studied to model a full proprietary Pick and Place manipulator inside it, and to develop custom ROS nodes to calculate trajectories; speaking of which, the URDF format is the standard to represent robots in ROS and the motion planning framework MoveIt offers user-friendly high-level methods. The communication between ROS and the Marchesini control architecture is established using the OPC UA standard; the tasks computed are transmitted offline to the PLC, supervisor controller of the physical robot, because the performances of the protocol don’t allow any kind of active control by ROS. Once the data are completely stored at the Marchesini side, the industrial PC makes the real robot execute a trajectory computed by MoveIt, so that it replicates the behaviour of the simulated manipulator in Rviz. Multiple experiments are performed to evaluate in detail the potential of ROS in the planning of movements for the company proprietary robots. The project ends with a small study regarding the use of ROS as a simulation platform. First, it is necessary to understand how a robotic application of the company can be reproduced in the Gazebo real world simulator. Then, a ROS node extracts information and examines the simulated robot behaviour, through the subscription to specific topics.

Robotic Manipulation of DLOs for Wiring Harness Assembly: a Machine Learning Approach

In recent times, a significant research effort has been focused on how deformable linear objects (DLOs) can be manipulated for real world applications such as assembly of wiring harnesses for the automotive and aerospace sector. This represents an open topic because of the difficulties in modelling accurately the behaviour of these objects and simulate a task involving their manipulation, considering a variety of different scenarios. These problems have led to the development of data-driven techniques in which machine learning techniques are exploited to obtain reliable solutions. However, this approach makes the solution difficult to be extended, since the learning must be replicated almost from scratch as the scenario changes. It follows that some model-based methodology must be introduced to generalize the results and reduce the training effort accordingly. The objective of this thesis is to develop a solution for the DLOs manipulation to assemble a wiring harness for the automotive sector based on adaptation of a base trajectory set by means of reinforcement learning methods. The idea is to create a trajectory planning software capable of solving the proposed task, reducing where possible the learning time, which is done in real time, but at the same time presenting suitable performance and reliability. The solution has been implemented on a collaborative 7-DOFs Panda robot at the Laboratory of Automation and Robotics of the University of Bologna. Experimental results are reported showing how the robot is capable of optimizing the manipulation of the DLOs gaining experience along the task repetition, but showing at the same time a high success rate from the very beginning of the learning phase.

Development of a Robotic Wires Storage System for Switchgear Manufacturing Automation

Considering the great development of robotics in industrial automation, the Remodel project aims to reproduce, through the use of Cobots, the wiring activity typical of a human operator and to realize an autonomous storage work. My researches focused on this second topic. In this paper, we will see how to realize a gripper compatible with an Omron TM5X-900, able to perform a pick and place of different types of cables, but also how to compute possible trajectories. In particular, what I needed, was a trajectory going from the Komax, the cables production machine, to a Warehouse taking into account the possible entangles of cables with the robot during its motion. The last part has been dedicated to the synchronization between robot and main machine work.

A comprehensive study on robotic manipulation of deformable linear objects

There are many deformable objects such as papers, clothes, ropes in a person’s living space. To have a robot working in automating the daily tasks it is important that the robot works with these deformable objects. Manipulation of deformable objects is a challenging task for robots because these objects have an infinite-dimensional configuration space and are expensive to model, making real-time monitoring, planning and control difficult. It forms a particularly important field of robotics with relevant applications in different sectors such as medicine, food handling, manufacturing, and household chores. In this report, there is a clear review of the approaches used and are currently in use along with future developments to achieve this task. My research is more focused on the last 10 years, where I have systematically reviewed many articles to have a clear understanding of developments in this field. The main contribution is to show the whole landscape of this concept and provide a broad view of how it has evolved. I also explained my research methodology by following my analysis from the past to the present along with my thoughts for the future.

Robotic grasping: State of the art and modular real-world implementation

Robotic Grasping is an important research topic in robotics since for robots to attain more general-purpose utility, grasping is a necessary skill, but very challenging to master. In general the robots may use their perception abilities like an image from a camera to identify grasps for a given object usually unknown. A grasp describes how a robotic end-effector need to be positioned to securely grab an object and successfully lift it without lost it, at the moment state of the arts solutions are still far behind humans. In the last 5–10 years, deep learning methods take the scene to overcome classical problem like the arduous and time-consuming approach to form a task-specific algorithm analytically. In this thesis are present the progress and the approaches in the robotic grasping field and the potential of the deep learning methods in robotic grasping. Based on that, an implementation of a Convolutional Neural Network (CNN) as a starting point for generation of a grasp pose from camera view has been implemented inside a ROS environment. The developed technologies have been integrated into a pick-and-place application for a Panda robot from Franka Emika. The application includes various features related to object detection and selection. Additionally, the features have been kept as generic as possible to allow for easy replacement or removal if needed, without losing time for improvement or new testing.

The Clinical Impact Of Cerebellar Grey Matter Pathology In Multiple Sclerosis.

The cerebellum is an important site for cortical demyelination in multiple sclerosis, but the functional significance of this finding is not fully understood. To evaluate the clinical and cognitive impact of cerebellar grey-matter pathology in multiple sclerosis patients. Forty-two relapsing-remitting multiple sclerosis patients and 30 controls underwent clinical assessment including the Multiple Sclerosis Functional Composite, Expanded Disability Status Scale (EDSS) and cerebellar functional system (FS) score, and cognitive evaluation, including the Paced Auditory Serial Addition Test (PASAT) and the Symbol-Digit Modalities Test (SDMT). Magnetic resonance imaging was performed with a 3T scanner and variables of interest were: brain white-matter and cortical lesion load, cerebellar intracortical and leukocortical lesion volumes, and brain cortical and cerebellar white-matter and grey-matter volumes. After multivariate analysis high burden of cerebellar intracortical lesions was the only predictor for the EDSS (p<0.001), cerebellar FS (p = 0.002), arm function (p = 0.049), and for leg function (p<0.001). Patients with high burden of cerebellar leukocortical lesions had lower PASAT scores (p = 0.013), while patients with greater volumes of cerebellar intracortical lesions had worse SDMT scores (p = 0.015). Cerebellar grey-matter pathology is widely present and contributes to clinical dysfunction in relapsing-remitting multiple sclerosis patients, independently of brain grey-matter damage.

Minimal Invasive Ostheosintesis For Treatment Of Diaphiseal Transverse Humeral Shaft Fractures.

To evaluate patients with transverse fractures of the shaft of the humerus treated with indirect reduction and internal fixation with plate and screws through minimally invasive technique. Inclusion criteria were adult patients with transverse diaphyseal fractures of the humerus closed, isolated or not occurring within 15 days of the initial trauma. Exclusion criteria were patients with compound fractures. In two patients, proximal screw loosening occurred, however, the fractures consolidated in the same mean time as the rest of the series. Consolidation with up to 5 degrees of varus occurred in five cases and extension deficit was observed in the patient with olecranon fracture treated with tension band, which was not considered as a complication. There was no recurrence of infection or iatrogenic radial nerve injury. It can be concluded that minimally invasive osteosynthesis with bridge plate can be considered a safe and effective option for the treatment of transverse fractures of the humeral shaft. Level of Evidence III, Therapeutic Study.

Comparative Cytogenetics Of Physalaemus albifrons And Physalaemus Cuvieri Species Groups (anura, leptodactylidae).

Recently, Physalaemus albifrons (Spix, 1824) was relocated from the Physalaemus cuvieri group to the same group as Physalaemus biligonigerus (Cope, 1861), Physalaemus marmoratus (Reinhardt & Lütken, 1862) and Physalaemus santafecinus Barrio, 1965. To contribute to the analysis of this proposition, we studied the karyotypes of Physalaemus albifrons, Physalaemus santafecinus and three species of the Physalaemus cuvieri group. The karyotype of Physalaemus santafecinus was found to be very similar to those of Physalaemus biligonigerus and Physalaemus marmoratus, which were previously described. A remarkable characteristic that these three species share is a conspicuous C-band that extends from the pericentromeric region almost to the telomere in the short arm of chromosome 3. This characteristic is not present in the Physalaemus albifrons karyotype and could be a synapomorphy of Physalaemus biligonigerus, Physalaemus marmoratus and Physalaemus santafecinus. The karyotype of Physalaemus santafecinus is also similar to those of Physalaemus marmoratus and Physalaemus biligonigerus owing to the presence of several terminal C-bands and the distal localization of the NOR in a small metacentric chromosome. In contrast, the Physalaemus albifrons karyotype has no terminal C-bands and its NOR is located interstitially in the long arm of submetacentric chromosome 8. The NOR-bearing chromosome of Physalaemus albifrons very closely resembles those found in Physalaemus albonotatus (Steindachner, 1864), Physalaemus cuqui Lobo, 1993 and some populations of Physalaemus cuvieri Fitzinger, 1826. Additionally, the Physalaemus albifrons karyotype has an interstitial C-band in chromosome 5 that has been exclusively observed in species of the Physalaemus cuvieri group. Therefore, we were not able to identify any chromosomal feature that supports the reallocation of Physalaemus albifrons.