Collision avoidance and dynamic modeling for wheeled mobile robots and industrial manipulators

Collision Avoidance and Dynamic Modeling are key topics for researchers dealing with mobile and industrial robotics. A wide variety of algorithms, approaches and methodologies have been exploited, designed or adapted to tackle the problems of finding safe trajectories for mobile robots and industrial manipulators, and of calculating reliable dynamics models able to capture expected and possible also unexpected behaviors of robots. The knowledge of these two aspects and their potential is important to ensure the efficient and correct functioning of Industry 4.0 plants such as automated warehouses, autonomous surveillance systems and assembly lines. Collision avoidance is a crucial aspect to improve automation and safety, and to solve the problem of planning collision-free trajectories in systems composed of multiple autonomous agents such as unmanned mobile robots and manipulators with several degrees of freedom. A rigorous and accurate model explaining the dynamics of robots, is necessary to tackle tasks such as simulation, torque estimation, reduction of mechanical vibrations and design of control law

Preliminary analysis of energy recovery from fluxes in treatment and depuration structures

reservedAnalisi preliminare di recupero energetico da flussi in impianti di trattamento e depurazion

Velocity Obstacle-based Trajectory Planner for Two-Link Planar Manipulators

Velocity Obstacle paradigm is one of the most popular and studied decentralized trajectory planning methods for multi-agent systems moving in dynamic environments. It has been successfully used in a multitude of real and simulated scenarios for the collision-free maneuver of ground or aerial mobile robots. In this paper we address the problem of adapting Velocity Obstacles to provide collision-free trajectories also for robotic manipulators with dynamic obstacles in their workspace. Simulation results show the effectiveness of the proposed approach

Planning with Real-Time Collision Avoidance for Cooperating Agents under Rigid Body Constraints

In automated warehouses, path planning is a crucial topic to improve automation and efficiency. This kind of planning is usually computed off-line knowing the planimetry of the warehouse and the starting and target points of each agent. However, this global approach is not able to manage unexpected static/dynamic obstacles and other agents moving in the same area. For this reason in multi-robot systems global planners are usually integrated with local collision avoidance algorithms. In this paper we use the Voronoi diagram as global planner and the Velocity Obstacle (VO) method as collision avoidance algorithm. The goal of this paper is to extend such hybrid motion planner by enforcing mechanical constraints between agents in order to execute a task that cannot be performed by a single agent. We will focus on the cooperative task of carrying a payload, such as a bar. Two agents are constrained to move at the end points of the bar. We will improve the original algorithms by taking into account dynamically the constrained motion both at the global and at the collision avoidance level

A Brownian–Markov stochastic model for cart-like wheeled mobile robots

Wheeled mobile robots are commonly used in a wide range of applications from automated warehouses to patrolling. A rigorous and accurate model describing their dynamics is then important for control and tracking. It is worth mentioning that the majority of these models in literature deal with determinis-tic settings. Therefore, they are not able to take into account stochastic uncertainty or non-predictable phenomena such as lateral grip loss. In this paper, we present a novel stochastic dynamic model which considers random perturbations, while also considering the effect of unknown dissipative external forces acting on wheeled mobile robots. In particular, our approach is based on a two-state hybrid system of Stochastic Differential Equations modeling the robot dynamics subject to Brownian motion noises, with transitions from one state to the other triggered by to a homogeneous Markov chain. (c) 2023 European Control Association. Published by Elsevier Ltd. All rights reserved

Gray-Box Model Identification and Payload Estimation for Delta Robots

Delta Robots belong to a class of parallel robots widely used in industrial production processes, mostly for pick-and-place operations. The most relevant characteristics are the high speed and the extremely favorable ratio between the maximum payload and the weight of the robot itself. A reliable dynamic model is needed to implement torque controllers that reduce unnecessary high accelerations and so mechanical vibrations. Moreover, when the mass of the pickable object is unknown, it is crucial to identify with sufficient precision the dynamic contribution of the payload and to accordingly adapt the dynamic model in order to guarantee high performance

A novel inverse dynamic model for 3-DoF delta robots

Delta Robots belong to a class of parallel robots widely used in industrial production processes, mostly for pick-and-place operations. The most relevant characteristics are the high speed and the extremely favorable ratio between the maximum payload and the weight of the robot itself. A reliable dynamic model is needed to implement torque controllers that reduce unnecessary high accelerations and so mechanical vibrations. The state-of-art inverse dynamic models exploit simplifications in order to facilitate the derivation of the equations of motion and their implementation. In this work, a novel and more rigorous inverse dynamic model is presented which does not rely on simplifications of the kinematic structure. The model has been validated comparing its estimations with real torques data collected moving a Delta Robot D3-1200 by SIPRO Srl; the computational complexity of the algorithm has also been investigated

Retrospective study on the surveillance on dairy cows infective abortions in Northeastern Italy from 2006 to 2019

Objectives: Bovine abortion is an important cause of economic loss in dairy cattle, and has important implications in public veterinary health. Veneto region, in Northeastern Italy, has implemented since year 2006 an official surveillance plan on abortion in dairy cattle. The aim of this study is to describe the results of this surveillance, from 2006 to 2019, and to provide information about the occurrence of abortive pathogens and their prevalence. Material and methods: Aborted fetuses, accompanied by the dam’s blood sample, were delivered to the Regional State Veterinary Laboratory (IZSVe), and submitted to a panel of laboratory tests. The cows’ sera were tested for antibodies against Neospora caninum, Chlamydophila abortus, Coxiella burnetii, IBR virus, and BVD non structural protein NS2-3 by mean of commercial ELISA tests, and to Brucella abortus and melitensis following the EU regulation mandatory method. Antibody against Coxiella burnetii were detected using also the complement fixation test according to OIE guideline. On all the fetuses were performed necroscopy, microbiological culture from abomasum, histopathology from lung, and detection, by PCR from spleen, of BVD virus, Chlamydia spp., and Coxiella. burnetii. Detection of Neospora caninum by PCR from the brain was performed only on fetuses older than four month. Brucella spp isolation was carried out only if the abortion occurred after the fifth pregnancy month; while Campylobacter fetus isolation was performed on abortions occurred before the fifth month. A PCR for the detection of Schmallenberg virus from the brain was introduced after year 2013. Results: During these years (2006-2019) 4,562 bovine abortions were delivered to IZSVe, 668 of them were under the fifth month of gestation (14.6%). The most of fetuses delivered were autolytic (62.7%), without macroscopic lesions (30.8%) or mummified (4.5%). Histologically lung inflammatory lesions were present in 32.8% of cases. An infective agent was detected in 1451 fetuses (31.8%). Neospora caninum was the most frequent specific abortion agent isolated (22.2%), followed by BVD virus (5.7%), Coxiella. Burnetii (4.7%) and Chlamydia spp (0.7%). Schmallenberg virus was detected only in 3 fetuses delivered respectively in year 2012, 2013 and 2014, but only one showed congenital abnormalities (limbs arthrogryposis and jaw malformation). Microbiological culture was considered positive only when specific abortifacient pathogens were isolated: according to this criteria the 13% had a culture positive test. Among the bacteriological agents isolated the most relevant were T. pyogenes (47.4%), Bacillus spp. (29.4%), Streptococcus spp. (15.8%), L. monocytogenes and fungi (1.9%), P. multocida (1.7%), Salmonella spp. (1.1%), M. haemolytica (0.7%), Corynebacterium spp. (0.2%). Campylobacter fetus was isolated in one abortion and Brucella spp. was never isolated. Serological tests showed a high percentage of cows had antibodies against BVD virus (44.8%), Chlamydophila abortus (41.3%), Neospora caninum (33.2%); IBR virus (25.4%), C. burnetii (15.8%). All tested sera and abortions were negative for Brucella spp. The agreement between serological test and PCR for Neospora caninum was substantial (Cohen’s kappa (k) = 0.667, while the agreement for BVD virus and C. burnetii was slight (k = 0.11; k = 0.16). Conclusions: In our opinion, the abortion surveillance program provided many useful and interesting information about the health status of dairy farms and the diagnostic methods suitable for abortion diagnosis. Necroscopy findings showed the low prevalence of specific macroscopic lesion in fetuses, highlighting the importance to use a standardized protocol including tests for detection of the most relevant abortion agents. Infective abortions should be expected approximately in 30% of cases, several other causes should be considered as the source of pregnancy interruption. In order of importance Neospora caninum is the major abortive pathogen in Northeastern Italy, bacterial or fungal agents are the second, with prevalence ranging from 12-14%, while BVD virus and Coxiella. burnetii are less likely to be isolated