2,135 research outputs found
Occupational health and safety issues in human-robot collaboration: State of the art and open challenges
Human-Robot Collaboration (HRC) refers to the interaction of workers and robots in a shared workspace. Owing to the integration of the industrial automation strengths with the inimitable cognitive capabilities of humans, HRC is paramount to move towards advanced and sustainable production systems. Although the overall safety of collaborative robotics has increased over time, further research efforts are needed to allow humans to operate alongside robots, with awareness and trust. Numerous safety concerns are open, and either new or enhanced
technical, procedural and organizational measures have to be investigated to design and implement inherently safe and ergonomic automation solutions, aligning the systems performance and the human safety. Therefore, a bibliometric analysis and a literature review are carried out in the present paper to provide a comprehensive overview of Occupational Health and Safety (OHS) issues in HRC. As a result, the most researched topics and application areas, and the possible future lines of research are identified. Reviewed articles stress the central role
played by humans during collaboration, underlining the need to integrate the human factor in the hazard analysis and risk assessment. Human-centered design and cognitive engineering principles also require further investigations to increase the worker acceptance and trust during collaboration. Deepened studies are compulsory in the healthcare sector, to investigate the social and ethical implications of HRC. Whatever the application context is, the implementation of more and more advanced technologies is fundamental to overcome the current HRC safety concerns, designing low-risk HRC systems while ensuring the system productivity
Multidisciplinary perspectives on Artificial Intelligence and the law
This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio
Sizing the Actuators for a Dragon Fly Prototype
In order to improve the design of the actuators of a Dragon Fly prototype, we study the loads applied to the actuators in operation. Both external and inertial forces are taken into account, as well as internal loads, for the purposes of evaluating the influence of the compliance of the arms on that of the "end-effector". We have shown many inadequacies of the arms regarding the stiffness needed to meet the initial design requirements. In order to reduce these inadequacies, a careful structural analysis of the stiffness of the actuators is carried out with a FEM technique, aimed at identifying the design methodology necessary to identify the mechanical elements of the arms to be stiffened. As an example, the design of the actuators is presented, with the aim of proposing an indirect calibration strategy. We have shown that the performances of the Dragon Fly prototype can be improved by developing and including in the control system a suitable module to compensate the incoming errors. By implementing our model in some practical simulations, with a maximum load on the actuators, and internal stresses, we have shown the efficiency of our model by collected experimental data. A FEM analysis is carried out on each actuator to identify the critical elements to be stiffened, and a calibration strategy is used to evaluate and compensate the expected kinematic errors due to gravity and external loads. The obtained results are used to assess the size of the actuators. The sensitivity analysis on the effects of global compliance within the structure enables us to identify and stiffen the critical elements (typically the extremities of the actuators). The worst loading conditions have been evaluated, by considering the internal loads in the critical points of the machine structure results in enabling us the sizing of the actuators. So that the Dragon fly prototype project has been set up, and the first optimal design of the arms has been performed by means of FEM analysis
Extension of the Control Concept for a Mobile Overhead Manipulator to Whole-Body Impedance Control
At present, robots constitute a central component of contemporary factories. The application of traditional ground-based systems, however, may lead to congested floors with minimal space left for new robots or human workers. Overhead manipulators, on the other hand, aim to occupy the unutilized ceiling space, in order to manipulate the workspace located below them. The SwarmRail system is an example of such an overhead manipulator. This concept deploys mobile units driving across a passive railstructure above the ground. Additionally, equipping the mobile units with robotic arms at their bottom side enables this design to provide continuous overhead manipulation while in motion. Although a first demonstrator confirmed the functional capability of said system, the current hardware suffers from complications while traversing rail crossings. Due to uneven rails consecutive rails, said crossing points cause the robot's wheels to collide with the new rail segment it is driving towards. Additionally, the robot experiences an undesired sudden altitude change.
In this thesis, we aim to implement a hierarchical whole-body impedance tracking controller for the robots employed within the SwarmRail system. Our controller combines a kinematically controlled mobile unit with the impedance-based control of a robotic arm through an admittance interface. The focus of this thesis is set on the controller's robustness against the previously mentioned external disturbances. The performance of this controller is validated inside a simulation that incorporates the aforementioned complications. Our findings suggest, that the control strategy presented in this thesis provides a foundation for the development of a controller applicable to the physical demonstrator
Characterisation and State Estimation of Magnetic Soft Continuum Robots
Minimally invasive surgery has become more popular as it leads to less bleeding, scarring, pain, and shorter recovery time. However, this has come with counter-intuitive devices and steep surgeon learning curves. Magnetically actuated Soft Continuum Robots (SCR) have the potential to replace these devices, providing high dexterity together with the ability to conform to complex environments and safe human interactions without the cognitive burden for the clinician. Despite considerable progress in the past decade in their development, several challenges still plague SCR hindering their full realisation. This thesis aims at improving magnetically actuated SCR by addressing some of these challenges, such as material characterisation and modelling, and sensing feedback and localisation.
Material characterisation for SCR is essential for understanding their behaviour and designing effective modelling and simulation strategies. In this work, the material properties of commonly employed materials in magnetically actuated SCR, such as elastic modulus, hyper-elastic model parameters, and magnetic moment were determined. Additionally, the effect these parameters have on modelling and simulating these devices was investigated.
Due to the nature of magnetic actuation, localisation is of utmost importance to ensure accurate control and delivery of functionality. As such, two localisation strategies for magnetically actuated SCR were developed, one capable of estimating the full 6 degrees of freedom (DOFs) pose without any prior pose information, and another capable of accurately tracking the full 6-DOFs in real-time with positional errors lower than 4~mm. These will contribute to the development of autonomous navigation and closed-loop control of magnetically actuated SCR
Safety-Aware Human-Robot Collaborative Transportation and Manipulation with Multiple MAVs
Human-robot interaction will play an essential role in various industries and
daily tasks, enabling robots to effectively collaborate with humans and reduce
their physical workload. Most of the existing approaches for physical
human-robot interaction focus on collaboration between a human and a single
ground robot. In recent years, very little progress has been made in this
research area when considering aerial robots, which offer increased versatility
and mobility compared to their grounded counterparts. This paper proposes a
novel approach for safe human-robot collaborative transportation and
manipulation of a cable-suspended payload with multiple aerial robots. We
leverage the proposed method to enable smooth and intuitive interaction between
the transported objects and a human worker while considering safety constraints
during operations by exploiting the redundancy of the internal transportation
system. The key elements of our system are (a) a distributed payload external
wrench estimator that does not rely on any force sensor; (b) a 6D admittance
controller for human-aerial-robot collaborative transportation and
manipulation; (c) a safety-aware controller that exploits the internal system
redundancy to guarantee the execution of additional tasks devoted to preserving
the human or robot safety without affecting the payload trajectory tracking or
quality of interaction. We validate the approach through extensive simulation
and real-world experiments. These include as well the robot team assisting the
human in transporting and manipulating a load or the human helping the robot
team navigate the environment. To the best of our knowledge, this work is the
first to create an interactive and safety-aware approach for quadrotor teams
that physically collaborate with a human operator during transportation and
manipulation tasks.Comment: Guanrui Li and Xinyang Liu contributed equally to this pape
Machine Learning Meets Advanced Robotic Manipulation
Automated industries lead to high quality production, lower manufacturing
cost and better utilization of human resources. Robotic manipulator arms have
major role in the automation process. However, for complex manipulation tasks,
hard coding efficient and safe trajectories is challenging and time consuming.
Machine learning methods have the potential to learn such controllers based on
expert demonstrations. Despite promising advances, better approaches must be
developed to improve safety, reliability, and efficiency of ML methods in both
training and deployment phases. This survey aims to review cutting edge
technologies and recent trends on ML methods applied to real-world manipulation
tasks. After reviewing the related background on ML, the rest of the paper is
devoted to ML applications in different domains such as industry, healthcare,
agriculture, space, military, and search and rescue. The paper is closed with
important research directions for future works
Study of an UAV implementation for solar panel cleaning
This bachelor final thesis delves into the computational resolution of transport equations, with a focus on introducing the student to Computational Fluid Dynamics (CFD) simulations. The objective of this research is achieved through the development of custom codes capable of solving problems presented by the Heat and Mass Transfer Technological Center (CTTC) [1] at the Technical University of Catalonia (UPC). Using the Finite Volume Method (FVM) and an algorithm based on the Fractional Step Method (FSM) for incompressible fluids, the equations of mass, momentum, and energy are solved. The student has personally programmed and verified all the codes using the C++ language. Special attention is given to comprehending the theoretical and computational implications of the Navier-Stokes equations, with a deliberate selection of progressively challenging problems that cover various aspects of these equations, culminating in the study of turbulence. The investigation extensively analyzes the contribution of convective and diffusive terms, beginning with the solution of a pure diffusion case and progressing to the numerical solution of a general convection-diffusion equation. Additionally, the study focuses on applied cases relevant to the aerospace industry, such as airflow around airfoils and cooled blades. However, this work only considers the convective and diffusive terms, as its primary goal is to lay the foundation for a future model examining the feasibility of hydrogen-powered aircraft engines in terms of turbine blade material resistance. The Fractional Step Method is applied to solve both internal flow scenarios, encompassing forced and natural convection, and external flow situations, specifically the flow around a square cylinder. The research investigates various aspects of turbulence and implements them in resolving the Burgers equation and a three-dimensional channel flow. Concluding the thesis, a proposal for future steps is presented, outlining an advanced research project that involves an in-depth exploration of turbulence models and the utilization of High Performance Computing (HPC)
Improving Automated Operations of Heavy-Duty Manipulators with Modular Model-Based Control Design
The rapid development of robotization and automation in mobile working machines aims to increase productivity and safety in many industrial sectors. In heavy-duty applications, hydraulically actuated manipulators are the common solution due to their large power-to-weight ratio. As hydraulic systems can exhibit nonlinear dynamic behavior, automated operations with closed-loop control become challenging. In industrial applications, the dexterity of operations for manipulators is ensured by providing interfaces to equip product variants with different tool attachments. By considering these domain-specific tool attachments for heavy-duty hydraulic manipulators (HHMs), the autonomous robotic operating development for all product variants might be a time-consuming process.
This thesis aims to develop a modular nonlinear model-based (NMB) control method for HHMs to enable systematic NMB model reuse and control system modularity across different HHM product variants with actuators and tool attachments. Equally importantly, the properties of NMB control are used to improve the high-performance control for multi degrees-of-freedom robotic HHMs, as rigorously stability-guaranteed control systems have been shown to provide superior performance. To achieve these objectives, four research problems (RPs) on HHM controls are addressed. The RPs are focused on damping control methods in underactuated tool attachments, compensating for static actuator nonlinearities, and, equally significantly, improving overall control performance. The fourth RP is introduced for hydraulic series elastic actuators (HSEAs) in HHM applications, which can be regarded as supplementing NMB control with the aim of improving force controllability.
Six publications are presented to investigate the RPs in this thesis. The control development focus was on modular NMB control design for HHMs equipped with different actuators and tool attachments consisting of passive and actuated joints. The designed control methods were demonstrated on a full-size HHM and a novel HSEA concept in a heavy-duty experimental setup. The results verified that modular control design for HHM systems can be used to decrease the modifications required to use the manipulator with different tool attachments and floating-base environments
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