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In the not-too-distant future, humans will return to the Moon and step foot for the first time on Mars. Eventually, humanity will colonize these celestial bodies, where living and working will be commonplace. Energy is fundamental to all life. The energy that people use to sustain themselves on Earth, and in particular on these other worlds, is the integrated, safe production of electrical power, day and night. This paper proposes a radically new solution to this problem: Solar Tracking by day and a Solar Rechargeable Calcium Oxide Chemical Thermoelectric Reactor by night. Called the "Robotic End Effector for Lunar and Martian Geological Exploration of Space" (REEGES) Day/Night Power Generator Station, this form of thermoelectric power generation is mathematically modeled, simulation is performed, and a concept model design is demonstrated in this paper. The results of the presented simulation show the maximum total system output capability is 9.89 V, 6.66 A, and 65.9 W, with an operating time of up to 12 h, through a scalable design. This research provides instructions to the Space Research Community on a complete and novel development methodology for creating fully customized, configurable, safe, and reliable solar/thermoelectric day/night power generators, specifically meant for use on the Moon and Mars, using the Proportional-Integral-Derivative++ (PID++) Humanoid Motion Control Algorithm for its operation on a computationally lightweight microcontroller. [ABSTRACT FROM AUTHOR]

The rail industry is constantly facing challenges related to safety with regard to the detection of surface cracks and internal defects within rail tracks. Significant focus has been placed on developing sensor technologies that would facilitate the detection of flaws that compromise rail safety. In parallel, robot automation has demonstrated significant advancements in the integration of sensor technologies within end effectors. This study investigates the novel integration of an ultrasonic sensor within a robotic platform specifically for the application of detecting surface cracks and internal defects within rail tracks. The performance of the robotic sensor system was assessed on a rail track specimen containing sacrificial surface cracks and internal defects and then compared against a manual detection system. The investigation concludes that the robotic sensor system successfully identified internal defects in the web region of the rail track when utilising a 60° and 70° wedged probe, with a frequency range between 4 MHz and 5 MHz. However, the surface crack investigation proved that the transducer was insensitive to the detection of cracks, possibly due to the inadequate angle of the wedged probe. The overall outcome of the study highlights the potential that robotic sensor systems have in the detection of internal defects and characterises the limitations of surface crack identification to assist in enhancing rail safety. [ABSTRACT FROM AUTHOR]

Fresh produce handling, particularly in final inspection and pack, is highly dependent on dextrous human labour. As part of a relatively low-profit margin industry, rising wage costs and labour shortages are impacting the viability of this sector and are a direct threat to global food security. Adoption of robotics is required to automate delicate handling tasks; this is a key goal for sustainable and profitable businesses that supply packed produce to consumers. This mini review considers the state of the art, as well as any developments required in robotic technology for the automation of inspection and packing of whole unprocessed fresh produce. There is a particular focus on robotic end effectors for the handling of fresh produce. We consider the role of soft robotics research in meeting hygiene and safety requirements, as well as the current limited range of end effectors for handling of highly varied and delicate produce types. Future directions are discussed based on the observation of available current technology available in research and the application to commercial practice. [ABSTRACT FROM AUTHOR]

A personal-computer-based and a Raspberry Pi single-board computer-based virtual force sensor with EtherCAT communication for a six-axis robotic arm are proposed in this paper. Both traditional mathematical modeling and machine learning techniques are used in the establishment of the dynamic model of the robotic arm. Thanks to the high updating rate of EtherCAT, the machine learning-based dynamic model on a personal computer achieved an average correlation coefficient between the estimated torque and the actual torque feedback from the motor driver of about 0.99. The dynamic model created using traditional mathematical modeling and the Raspberry Pi single-board computer demonstrates an approximate correlation coefficient of 0.988 between the estimated torque and the actual torque. The external torque observer is established by calculating the difference between the actual torque and the estimated torque, and the virtual force sensor converts the externally applied torques calculated for each axis to the end effector of the robotic arm. When detecting external forces applied to the end effector, the virtual force sensor demonstrates a correlation coefficient of 0.75 and a Root Mean Square Error of 12.93 N, proving its fundamental competence for force measurement. In this paper, both the external torque observer and the virtual force control are applied to applications related to sensing external forces of the robotic arm. The external torque observer is utilized in the safety collision detection mechanism. Based on experimental results, the system can halt the motion of the robotic arm using the minimum external force that the human body can endure, thereby ensuring the operator's safety. The virtual force control is utilized to implement a position and force hybrid controller. The experimental results demonstrate that, under identical control conditions, the position and force hybrid controller established by the Raspberry Pi single-board computer achieves superior control outcomes in a constant force control scenario with a pressure of 40 N. The average absolute error is 9.62 N, and the root mean square error is 11.16 N when compared to the target pressure. From the analysis of the results, it can be concluded that the Raspberry Pi system implemented in this paper can achieve a higher control command update rate compared to personal computers. As a result, it can provide greater control benefits in position and force hybrid control. [ABSTRACT FROM AUTHOR]

The end effector plays a critical role in fruit picking by a robotic fruit harvesting system. A newly developed vacuum-based robotic apple harvesting system, using the twist-and-pull fruit picking method, has shown promise in picking fruit from clusters and navigating through the tree canopies. The robot's original thin foam end effector failed to achieve acceptable picking performance because it was unable to conform to fruit of different sizes and thus could not generate sufficient suction forces needed to detach fruit. This research was therefore aimed at developing new end effectors to greatly enhance the robot's fruit picking performance. Field manual pulling and twisting experiments for three varieties of apples were conducted, and the critical pulling or suction force and twisting torque needed to detach 95% of apples were determined to be 28.3 N and 0.257 N-m (equivalent to a pulling force of 21.0 N for the current robot's configuration), respectively. Three new silicone-based end effectors of different geometries (denoted as "Straight", "Bellow" and "Curved") were designed and fabricated, and they were evaluated in lab and field experiments. Results showed that the three new end effectors performed significantly better than the original, unconformable end effector based on multiple performance metrics, including vacuum pressure, overall picking success rate, picking rate by the rotation mechanism, and fruit attachment orientation. The "Straight" end effector performed consistently better than the other two new end effectors; it had 87% overall picking success rate, 65% success rate by the rotation mechanism alone, and 89% success rate when the middle section or cheek of fruit attached to the end effector. With further improvements, the "Straight" end effector should meet the apple picking performance requirement for the new vacuum-based robotic harvesting system. [ABSTRACT FROM AUTHOR]

The combined effects of environmental factors such as high winds and melting ice can cause transmission line conductors to vibrate at high amplitudes, resulting in damaged pole structures, cracked insulating strands, and short circuits. The manual installation of electrical spacers between the two power line conductors is currently the only way to prevent this, but due to the high-voltage environment, this operation is extremely dangerous for a human worker. As a solution to automate this operation, the autonomous installation of electrical spacers using a robotic manipulator is proposed. For this purpose, a design of a special end effector for the robotic installation of electrical spacers is proposed. The end effector prototype was produced and tested under laboratory conditions and then used for the autonomous installation of spacers on power lines. Its localization with respect to the power lines is based on measurements of the magnetic field generated by the alternating currents flowing through the power lines. To verify the feasibility of the proposed solution under laboratory conditions, the proposed end effector equipped with magnetometers was developed and mounted on a 6-axis Schunk LWA 4p robotic arm. The implemented autonomous installation sequence was successfully verified using a robot and a laboratory mock-up of power lines. [ABSTRACT FROM AUTHOR]

The heat generated in reactor core is extracted using the sodium water heat exchanger system in fast breeder reactor. In the heat exchanger system there are 8 steam generators. Steam generator uses sodium and water to generate steam. Sodium–water reaction is exothermic in nature, so SG tubes need inspection to check healthiness of the tube. Due to space constraints, in-service inspection of SG needs remote-controlled robotic arm to locate SG tubes. The tube sheet is planar, so revolute joint two-link robotic arm is adapted. The movement of two-axis robotic arm needs control on position as well as velocity. The dynamic equation of two-axis robotic arm is coupled in nature which makes the control of end effector very difficult. The un-modeled phenomena, as that of friction and errors in mass distribution, will drastically affect the tracking of the end effector in the desired path. The Coriolis Effect is also accounted in the model. To precisely control the robotic arm end effector, the computed torque control technique is proposed and used in this paper. [ABSTRACT FROM AUTHOR]

It is essential to check whether the surgical robot end effector is safe to use due to phenomena such as linear buckling and mechanical resonance. The aim of this research is to build an multi criteria optimization model based on such criteria as the first natural frequency, buckling factor and mass, with the assumption of the basic constraint in the form of a safety factor. The calculations are performed for a serial structure of surgical robot end effector with six degrees of freedom ended with a scalpel. The calculation model is obtained using the finite element method. The issue of multi-criteria optimization is solved based on the response surface method, Pareto fronts and the genetic algorithm. The results section illustrates deformations of a surgical robot end effector occurring during the resonance phenomenon and the buckling deformations for subsequent values of the buckling coefficients. The dependencies of the geometrical dimensions on the criteria are illustrated with the continuous functions of the response surface, i.e. metamodels. Pareto fronts are illustrated, based on which the genetic algorithm finds the optimal quantities of the vector function. The conducted analyzes provide a basis for selecting surgical robot end effector drive systems from the point of view of their generated inputs. [ABSTRACT FROM AUTHOR]

The end effector plays a critical role in fruit picking by a robotic fruit harvesting system. A newly developed vacuum-based robotic apple harvesting system, using the twist-and-pull fruit picking method, has shown promise in picking fruit from clusters and navigating through the tree canopies. The robot's original thin foam end effector failed to achieve acceptable picking performance because it was unable to conform to fruit of different sizes and thus could not generate sufficient suction forces needed to detach fruit. This research was therefore aimed at developing new end effectors to greatly enhance the robot's fruit picking performance. Field manual pulling and twisting experiments for three varieties of apples were conducted, and the critical pulling or suction force and twisting torque needed to detach 95% of apples were determined to be 28.3 N and 0.257 N-m (equivalent to a pulling force of 21.0 N for the current robot's configuration), respectively. Three new silicone-based end effectors of different geometries (denoted as "Straight", "Bellow" and "Curved") were designed and fabricated, and they were evaluated in lab and field experiments. Results showed that the three new end effectors performed significantly better than the original, unconformable end effector based on multiple performance metrics, including vacuum pressure, overall picking success rate, picking rate by the rotation mechanism, and fruit attachment orientation. The "Straight" end effector performed consistently better than the other two new end effectors; it had 87% overall picking success rate, 65% success rate by the rotation mechanism alone, and 89% success rate when the middle section or cheek of fruit attached to the end effector. With further improvements, the "Straight" end effector should meet the apple picking performance requirement for the new vacuum-based robotic harvesting system. [ABSTRACT FROM AUTHOR]

Dual-arm robot manipulation is applicable to many domains, such as industrial, medical, and home service scenes. Learning from demonstrations is a highly effective paradigm for robotic learning, where a robot learns from human actions directly and can be used autonomously for new tasks, avoiding the complicated analytical calculation for motion programming. However, the learned skills are not easy to generalize to new cases where special constraints such as varying relative distance limitation of robotic end effectors for human-like cooperative manipulations exist. In this paper, we propose a dynamic movement primitives (DMPs) based skills learning framework for redundant dual-arm robots. The method, with a coupling acceleration term to the DMPs function, is inspired by the transient performance control of Barrier Lyapunov Functions. The additional coupling acceleration term is calculated based on the constant joint distance and varying relative distance limitations of end effectors for object-approaching actions. In addition, we integrate the generated actions in joint space and the solution for a redundant dual-arm robot to complete a human-like manipulation. Simulations undertaken in Matlab and Gazebo environments certify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In recent years, the agricultural sector has turned to robotic automation to deal with the growing demand for food. Harvesting fruits and vegetables is the most labor-intensive and time-consuming among the main agricultural tasks. However, seasonal labor shortage of experienced workers results in low efficiency of harvesting, food losses, and quality deterioration. Therefore, research efforts focus on the automation of manual harvesting operations. Robotic manipulation of delicate products in unstructured environments is challenging. The development of suitable end effectors that meet manipulation requirements is necessary. To that end, this work reviews the state-of-the-art robotic end effectors for harvesting applications. Detachment methods, types of end effectors, and additional sensors are discussed. Performance measures are included to evaluate technologies and determine optimal end effectors for specific crops. Challenges and potential future trends of end effectors in agricultural robotic systems are reported. Research has shown that contact-grasping grippers for fruit holding are the most common type of end effectors. Furthermore, most research is concerned with tomato, apple, and sweet pepper harvesting applications. This work can be used as a guide for up-to-date technology for the selection of suitable end effectors for harvesting robots. [ABSTRACT FROM AUTHOR]

Tactile feedback is relevant in a broad range of human–machine interaction systems (e.g. teleoperation, virtual reality and prosthetics). The available tactile feedback interfaces comprise few sensing and stimulation units, which limits the amount of information conveyed to the user. The present study describes a novel technology that relies on distributed sensing and stimulation to convey comprehensive tactile feedback to the user of a robotic end effector. The system comprises six flexible sensing arrays (57 sensors) integrated on the fingers and palm of a robotic hand, embedded electronics (64 recording channels), a multichannel stimulator and seven flexible electrodes (64 stimulation pads) placed on the volar side of the subject's hand. The system was tested in seven subjects asked to recognize contact positions and identify contact sliding on the electronic skin, using distributed anode configuration (DAC) and single dedicated anode configuration. The experiments demonstrated that DAC resulted in substantially better performance. Using DAC, the system successfully translated the contact patterns into electrotactile profiles that the subjects could recognize with satisfactory accuracy (i.e. median{IQR} of 88.6{11}% for static and 93.3{5}% for dynamic patterns). The proposed system is an important step towards the development of a high-density human–machine interfacing between the user and a robotic hand. This article is part of the theme issue 'Advanced neurotechnologies: translating innovation for health and well-being'. [ABSTRACT FROM AUTHOR]

Millimeter-scale continuum bending actuators are useful in minimally invasive surgery to allow distal visualization and manipulation outside the line of sight. This paper presents a new continuum bending actuator based on shape memory alloy (SMA) with variable bending length. It consists of two SMA wires antagonistically configured to produce bidirectional bending under Joule heating. A linearly actuated rigid tube along the longitudinal axis enables continuous bending length adjustment, thus enhancing its workspace and force range. The proposed fabrication method tackles the challenging assembly tasks of maintaining the antagonistic configuration of long SMA wires, and robust electrical and mechanical connection during actuation. A quasi-static model of the actuator based on beam model and SMA constitutive model is presented and verified. The bending actuator was evaluated comprehensively for its workspace, blocked force, and trajectory tracking capability at different bending lengths and under different cooling conditions. It is the first work that demonstrates real-time continuous bending length adjustment in SMA-based bending actuator, leading to the potential development of compact and compliant robotic end effectors with improved distal workspace and force. [ABSTRACT FROM AUTHOR]

In high power electrical machines, the leakage magnetic flux due to end windings induces eddy currents in clamping devices. However, it is quite difficult to quantify these losses. In order to study the effect of different clamping materials and the impact of the magnetization direction, an experimental mock-up composed of a stator and a clamping plate has been developed. An axial coil generates a circumferential magnetic flux in the stator core at different frequencies. Eddy current losses in the clamping plates are deduced from a power balance by subtracting Joule losses and iron losses from the total measured losses. Iron losses are deduced from 3D FE calculations while the impact of the frequency on B(H) curve is taken into account. Losses in the clamping device are then analyzed depending on experimental parameters. [ABSTRACT FROM AUTHOR]

The article presents a study that explores about the stretchable and strain-unperturbed pressure sensor for motion interference–free tactile monitoring on skins. It mentions about the capability to provide all the desired characteristics for quantitative pressure sensing on a deformable surface, sensor has been used to realize the accurate sensation of physical interactions on human or soft robotic skin.

This paper describes the design and development of a cleaning robot, using adaptive manufacturing technology and its use with a control algorithm for which there is a stability proof. The authors' goal was to fill the gap between theory and practical implementation based on available low-cost components. Adaptive manufacturing was chosen to cut down the cost of manufacturing the robot. Practical verification of the effectiveness of the control algorithm was achieved with the experiments. The robot comprises mainly three assemblies, a four-wheel-drive platform, a four-degrees-of-freedom robotic arm, and a vacuum system. The inlet pipe of the vacuum system was attached to the end effector of the robotic arm, which makes the robot more flexible to clean uneven areas, such as skirting on floors. The robot was equipped with a LIDAR sensor and web camera, giving the opportunity to develop more complex methods. A low-level proportional–integral–derivative (PID) speed controller was implemented, and a high-level controller that uses artificial potential functions to generate repulsive components, which avoids collision with obstacles. Robot operating system (ROS) was installed in the robot's on-board system. With the help of the ROS node, the high-level controller generates control signals for the low-level controller. [ABSTRACT FROM AUTHOR]