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Bicycle transmission systems represent a key component in the design of bicycles, as they determine the nature of pedaling effort that riders have to provide. Multi-gear systems enable riders to choose between multiple transmission ratios and are typically divided into external and internal. The present work aims at designing a three-speed automatic internal shifting hub for regular (non-electric) bicycles, starting from an already existing alternative with only two gear ratios (i.e., speeds), which is taken as reference. The complete kinematic design and a preliminary dimensioning are implemented and described in detail. The novelty of the design lays in the number of available gear rations (three), which is an unprecedented result for automatic internal shifting hubs for regular bicycles, as it is unmatched by the models available on the market. The higher number of gear rations increases the number of available combinations of torque and pedaling cadence to achieve a certain velocity, granting more riding flexibility and ultimately enabling easier rides. This is proven through validation by numerical simulation of a driving cycle, which shows that lower and more constant pedaling forces are required when using the novel three-speed automatic internal shifting hub with respect to the two-speed reference model.

Trajectory planning is a crucial and challenging problem for research on intelligent robotic and mechatronic systems, which play a pivotal role in modern manufacturing processes, and especially within the framework of Industry 4 [...]

Meeting ever-tightening emission regulations and ambitious climate targets requires drastic efficiency improvements and emission reduction across all sectors. Hybridization as an intermediary step towards electrification is a prominent approach to achieve this. Within the forestry sector, most equipment still relies on conventional mechanical or hydraulical drivetrains. This work focuses on the design of hybrid tower yarder drivetrains, in order to facilitate the technological transition to more sustainable equipment. Tower yarder duty cycle data are extracted from the literature and organized into a set of reference duty cycle data via Matlab simulations. Based on typical performance requirements, various technological solutions are studied for the following key tower yarder subsystems: energy storage, winch drive, energy source, and energy dissipation. The objective is to determine the most performing design considering system cost, performance, weight, and durability. Challenging control considerations are discussed and control algorithms are presented. Further presented are drivetrain architecture alternatives to boost overall efficiency. The best hybrid drivetrain, based on a large set of operation data gathered from other studies, is finally subjected to design calculations and a case study involving a 5-ton tower yarder. Results indicate that off-the-shelf electric drives, reduction gearing, and energy dissipation systems can satisfy all performance requirements, including a maximum power of about 100 kW per drive. A 15–45 kWh power-dense battery pack or a 100 kWh energy-dense battery pack may be required to cope with a power of up to 70 kW RMS, pointing to a need for substantial overdesign and confirming that the energy storage system represents the largest design challenge. The engine should achieve at least 41.5 kW of power to compensate for combined average net energy consumption in the yarder. These results confirm the feasibility of tower yarder hybridization and the large potential for energy recovery. This is especially true in the closed-loop setup, with a recovered energy of up to 5 kWh per transport cycle. Finally, differences between the proposed optimal design and the commercial hybrid design by Koller Forsttechnik are discussed.

Small-to-medium sized systems able to perform multiple operations are a promising option for use in agricultural robotics. With this in mind, we present the conceptualization and implementation of a versatile and modular unmanned ground vehicle prototype, which is designed on top of a commercial wheeled mobile platform, in order to test and assess new devices, and motion planning and control algorithms for different Precision Agriculture applications. Considering monitoring, harvesting and spraying as target applications, the developed system utilizes different hardware modules, which are added on top of a mobile platform. Software modularity is realized using the Robot Operating System (ROS). Self- and ambient-awareness, including obstacle detection, are implemented at different levels. A novel extended Boundary Node Method is used for path planning and a modified Lookahead-based Line of Sight guidance algorithm is used for path following. A first experimental assessment of the system’s capabilities in an emulated orchard scenario is presented here. The results demonstrate good path-planning and path-following capabilities, including cases in which unknown obstacles are present.

A survey was conducted on 12 cable yarding operations in northern Italy, with the purpose of determining fuel consumption and time use. The observation unit was the individual operation, intended as all the activities needed to complete the harvesting of a sale (mean = 500 m3 of timber). All teams were equipped with a tower yarder, an excavator-based loader or processor and a truck or a tractor with trailer, if intermediate transportation to a larger roadside landing (two-staging) was required. The crew size was 3 or 4 operators. Time and fuel use were recorded separately for the following tasks: relocation; set up & dismantle; commuting; yarding; processing and/or loading; major delay events. Fuel consumption averaged 5.1 L m−3, of which 2.2 L m−3 was incurred by two-staging. In general, the yarder accounted for less than half the total fuel consumption of the operation: the processor was indeed the main consumer. Relocation had a very small incidence on time and fuel use. Set up and dismantle did not incur significant fuel consumption but occupied a meaningful share of total time (mean = 22%). Commuting also incurred unexpectedly large (and generally neglected) fuel and time use—with means at 13% and 7%, respectively. Technology developments aimed at reducing fuel consumption should target both main consumers: the yarder as well as the excavator-based processor. Significant benefits would also be achieved through improved planning and infrastructure development, aimed at minimizing the need for intermediate transportation (i.e. two-staging).

Rotating machinery is fundamental in industry, gearboxes especially. However, failures may occur in their transmission components due to regular usage over long periods of time, even when operations are not intense. To avoid such failures, Structural Health Monitoring (SHM) techniques for damage prediction and in-advance detection can be applied. In this regard, correlations between measured signal variations and damage can be inspected using Artificial Intelligence (AI), which demands large numbers of data for training. Since obtaining signal samples of damaged components experimentally is currently unviable for complex systems due to destructive test costs, model-based numerical approaches are to be explored to solve this problem. To address this issue, this work applied an innovative hybrid Finite Element Method (FEM)–analytical approach, reducing computational effort and increasing performance with respect to traditional FEM. With this methodology, a system can be simulated with accuracy and without geometrical simplifications for healthy and damaged cases. Indeed, considering different positions and dimensions of damages (e.g., cracks) on the tooth roots of gears can offer new ways of damage investigation. As a reference to validate healthy systems and damage cases in terms of eigenfrequencies, a back-to-back test rig was used. Numerical simulations were performed for different cases, resulting in vibrational spectra for systems with no damage, with damage, and with damage of different intensities. The vibration spectra were used as data to train an Artificial Neural Network (ANN) to predict the machine state by Condition Monitoring (CM) and Fault Diagnosis (FD). For predicting the health and the intensity of damage to a system, classification and multi-class classification methods were implemented, respectively. Both sets of classification results presented good prediction agreement.

Enforcing the cessation of motion is a common action in robotic systems to avoid the damage that the robot can exert on itself, its environment or, in shared environments, people. This procedure raises two main concerns, which are addressed in this paper. On the one hand, the stopping procedure should respect the collision free path computed by the motion planner. On the other hand, a sudden stop may produce large current peaks and challenge the limits of the motor’s control capabilities, as well as degrading the mechanical performance of the system, i.e., increased wear. To address these concerns, we propose a novel method to enforce a mechanically feasible, smooth and path-consistent stop of the robot based on a time-minimization algorithm. We present a numerical implementation of the method, as well as a numerical study of its complexity and convergence. Finally, an experimental comparison with an off-the-shelf stopping scheme is presented, showing the effectiveness of the proposed method.

The use of flexible multibody simulation has increased significantly over recent years due to the increasingly lightweight nature of mechanical systems. The prominence of lightweight engineering design in mechanical systems is driven by the desire to require less energy in operation and to reach higher speeds. However, flexible lightweight systems are prone to vibration, which can affect reliability and overall system performance. Whether such issues are critical depends largely on the system eigenfrequencies, which should be correctly assigned by the proper choice of the inertial and elastic properties of the system. In this paper, an eigenfrequency assignment method for flexible multibody systems is proposed. This relies on a parametric modal model which is a Taylor expansion approximation of the eigenfrequencies in the neighborhood of a configuration of choice. Eigenfrequency assignment is recast as a quadratic programming problem which can be solved with low computational effort. The method is validated by assigning the lowest eigenfrequency of a two-bar linkage by properly adding point masses. The obtained results indicate that the proposed method can effectively assign the desired eigenfrequency.

Performance, efficiency and economy drive the design of mechanical systems and structures and has led lightweight engineering design to prominence [...]

The optimal design of damping parameters for passive vibration control remains a challenge for both research and industrial applications. Here, we introduce a design methodology based on limit cycle analysis in concert with design optimization. A state-space representation is used to model the vibrational behavior converged to its limit cycle. The design approach is outlined and applied to mechanical systems undergoing periodic forces. This method is applicable to both vibration mitigation and energy harvesting, and examples of both are shown. We conclude with a summary of the results and an outlook for future developments and applications.

Nowadays, the wire harness assembly process is still manually performed due to the process complexity and product variability (e.g., wires of different kind, size and length). The Wire cobots project, in which this work was conceived, aims at improving the current state-of-art assembly process by introducing in it collaborative robotics. A shared workstation exploiting human abilities and machine strengths was developed to assembly automotive wire harness by means of insulated tape for a real industrial case. In the new workstation, the human deals with the complex task of wire handling, while the robot performs the repetitive and strenuous taping operations. Such a task allocation together with the workstation redesign allow for an improvement of the operator’s well-being in terms of postural conditions and for an increase of the production efficiency. In this paper, the mechanical and mechatronic design, as well as the realization and validation of this new collaborative workstation are presented and discussed.

This paper describes a method for reducing the energy consumption of industrial robots and electrically actuated mechanisms performing cyclic tasks. The energy required by the system is reduced by outfitting it with additional devices able to store and recuperate energy, namely, compliant elements coupled in parallel with axles and regenerative motor drives. Starting from the electromechanical model of the modified system moving following a predefined periodic path, the relationship between the electrical energy and the stiffness and preload of the compliant elements is analyzed. The conditions for the compliant elements to be optimal are analytically derived. It is demonstrated that under these conditions the compliant elements are always beneficial for reducing the energy consumption. The effectiveness of the design method is verified by applying it to two test cases: a five-bar mechanism and a SCARA robot. The numerical validations show that the system energy consumption can be reduced up to the 77.8% while performing a high-speed, standard, not-optimized trajectory.

Human–robot interaction is an important aspect of Industry 4.0, and the extended use of robotics in industrial environments will not be possible without enabling them to safely interact with humans. This imposes relevant constraints in the qualitative characterization of the motions of robots when sharing their workspace with humans. In this paper, we address the trade-off between two such constraints, namely the smoothness, which is related to the cognitive stress that a person undergoes when interacting with a robot, and the speed, which is related to normative safety requirements. Given an execution time, such an approach will allow us to plan safe trajectories without neglecting cognitive ergonomics and production efficiency aspects. We first present the methodology able to express the balance between these qualities in the form of a composite objective function. Thanks to the variational formalism, we identify the related set of optimal trajectories with respect to the given criterion and give a suitable parametrization to them. Then, we are able to formulate the safety requirements in terms of a reparametrization of the motion. Finally, numerical and experimental results are provided. This allows the identification of the preferable sets of the possible motions that satisfy the operator’s psychological well-being and the assembly process performance by complying with the safety requirements in terms of mechanical risk prevention.

Enhancing energy efficiency is one of the main challenges of today’s industrial robotics and manufacturing technology. In this paper a task-related analysis of the energetic performance of a 4-DOF industrial parallel robot is presented, and the optimal location of a predefined task with respect to the robot workspace is investigated. An optimal position of the task relative to the robot can indeed reduce the actuators’ effort and the energy consumption required to complete the considered operation. The dynamic and electro-mechanical models of the manipulators are developed and implemented to estimate the energy consumption of a parametrized motion with trapezoidal speed profile, i.e., a pick-and-place operation. Numerical results provide energy consumption maps that can be adopted to place the starting and ending points of the task in the more energy-efficient location within the robot workspace.

The vibrational behavior of components in mechanical systems like drives and robots can become critical under changes in the system properties or loading in operation. Such undesired vibration can lead to detrimental conditions including excess wear, fatigue, discomfort, and acoustic emissions. Systems are designed to avoid certain frequencies to avoid such problems, but system parameters can change during operation due damage, wear, or change in loading. An example is the change in system properties or operation state that then activates resonance frequencies in our system. Therefore, this work has the goal of modifying the modal behavior of a system to avoid vibrational problems. Methods of design optimization are applied to find a new optimum design for this altered condition. Here, this is limited to the addition of mass in order to move the resonance frequency out of critical ranges. This though requires a new formulation of the optimization problem. We propose a new constraint formulation to avoid frequency ranges. To increase efficiency, a reduced analytical sensitivity analysis is introduced. This methodology is demonstrated on two test cases: a two-mass oscillator followed by a test case of higher complexity which is a gear housing considering over 15,000 design variables. The results show that the optimization solution gives the position and amount of mass added, which is a discrete solution that is practically implementable.

Within the vastness of the plant species, certain living systems show tendril structures whose motion is of particular interest for biomimetic engineers. Tendrils sense and coil around suitable grips, and by shortening in length, they erect the remaining plant body. To achieve contraction, tendrils rotate along their main axis and shift from a linear to a double-spring geometry. This phenomenon is denoted as the free-coiling phase. In this work, with the aim of understanding the fundamentals of the mechanics behind the free coiling, a reverse-engineering approach based on the finite element method was firstly applied. The model consisted of an elongated cylinder with suitable material properties, boundary, and loading conditions, in order to reproduce the kinematics of the tendril. The simulation succeeded in mimicking coiling faithfully and was therefore used to validate a tentative linear actuator model based on the plant’s working principle. More in detail, exploiting shape memory alloy materials to obtain large reversible deformations, the main tendril features were implemented into a nickel-titanium spring-based testing model. The results of the experimental tests confirmed the feasibility of the idea in terms of both functioning principles and actual performance. It can be concluded that the final set-up can be used as a base for a prototype design of a new kind of a linear actuator.

Energy saving in robotic and mechatronic systems is becoming an evermore important topic in both industry and academia. One strategy to reduce the energy consumption, especially for cyclic tasks, is exploiting natural motion. We define natural motion as the system response caused by the conversion of potential elastic energy into kinetic energy. This motion can be both a forced response assisted by a motor or a free response. The application of the natural motion concepts allows for energy saving in tasks characterized by repetitive or cyclic motion. This review paper proposes a classification of several approaches to natural motion, starting from the compliant elements and the actuators needed for its implementation. Then several approaches to natural motion are discussed based on the trajectory followed by the system, providing useful information to the researchers dealing with natural motion.

In recent years, new surgical tools have been designed to improve treatment results and lower patient trauma. Nevertheless, the dexterity and accuracy required for the positioning of new tools are often unreachable, if surgeons are not assisted by suitable systems. Significant advantages are derived from the introduction of computer and robot technologies. For that reason, the interaction between robotic systems and surgeons today is producing new interest worldwide both in medical and engineering fields. In particular, medical robotics has found fruitful ground in neurosurgical applications, since the high functional density of the central nervous system requires strict accuracy constraints on tool positioning. As a matter of fact, the major benefits of robots, such as precision, accuracy and repeatability, make them ideal as neurosurgeons’ assistants. This paper presents a master-slave haptic robotic system for minimally invasive neurosurgery, which can aid surgeons in performing safer and more accurate stereotactic neurosurgical treatments. The design of the proposed system is based on LANS (Linear Actuator for NeuroSurgery), which has been developed by our Research Group. Experimental test aimed at showing the added value of the DAANS system over its predecessor, the effectiveness of conformational caps and of the added rotational degree of freedom are scheduled for the upcoming months.

In the space environment the absence of gravity calls for constant safe attachment of any loose object, but the low-pressure conditions prohibit the use of glue-type adhesives. The attachment system of freely hunting spiders, e.g. Evarcha arcuata, employs van der Waals forces and mechanical interlocking. Furthermore, detachment is achieved passively and requires little force. Hence, the spider serves as a model for a versatile legged robot for space applications, e.g. on the outer surface of a space station. In this paper, we analyse the dry attachment systems of E. arcuata and geckos as well as the kinematics of freely hunting spiders. We generalise the results of biological studies on spider locomotion and mobility, including the major movement and the position constraints set by the dry adhesion system. From these results, we define a simplified spider model and study the overall kinematics of the legs both in flight and in contact with the surface. The kinematic model, the data on spider gait characteristics and the adhesion constraints are implemented in a kinematic simulator. The simulator results confirm the principal functionality of our concept.

In the last decades, increasing energy prices and growing environmental awareness have driven engineers and scientists to find new solutions for reducing energy consumption in manufacturing. Although many processes of a high energy consumption (e.g., chemical, heating, etc.) are considered to have reached high levels of efficiency, this is not the case for many other industrial manufacturing activities. Indeed, this is the case for robotic and automatic systems, for which, in the past, the minimization of energy demand was not considered a design objective. The proper design and operation of industrial robots and automation systems represent a great opportunity for reducing energy consumption in the industry, for example, by the substitution with more efficient systems and the energy optimization of operation. This review paper classifies and analyses several methodologies and technologies that have been developed with the aim of providing a reference of existing methods, techniques and technologies for enhancing the energy performance of industrial robotic and mechatronic systems. Hardware and software methods, including several subcategories, are considered and compared, and emerging ideas and possible future perspectives are discussed.

Thermally comfortable indoor environments are of great importance, as modern lifestyles often require people to spend more than 20 h per day indoors. Since most of the thermal comfort models use a variety of different environmental and personal factors that need to be measured or estimated, real-time and continuous assessment of thermal comfort is often not practically feasible. This work presents a cheap and non-invasive approach based on infrared imaging for monitoring the occupants’ thermal sensation and comfort in real time. Thanks to a mechatronic device developed by the authors, the imaging is performed on the forehead skin, selected because it is always exposed to the environment and, thus, facilitating the monitoring activity in a non-invasive manner. Tests have been performed in controlled conditions on ten subjects to assess the hypothesis that the forehead temperature is correlated with subjects’ thermal sensation. This allows the exploitation of this quantity as a base for a simple monitoring of thermal comfort, which could later be tuned with an extensive experimental campaign.