Manipulation Operations Research Articles

Do robots outperform humans in human-centered domains?

The incessant progress of robotic technology and rationalization of human manpower induces high expectations in society, but also resentment and even fear. In this paper, we present a quantitative normalized comparison of performance, to shine a light onto the pressing question, "How close is the current state of humanoid robotics to outperforming humans in their typical functions (e.g., locomotion, manipulation), and their underlying structures (e.g., actuators/muscles) in human-centered domains?" This is the most comprehensive comparison of the literature so far. Most state-of-the-art robotic structures required for visual, tactile, or vestibular perception outperform human structures at the cost of slightly higher mass and volume. Electromagnetic and fluidic actuation outperform human muscles w.r.t. speed, endurance, force density, and power density, excluding components for energy storage and conversion. Artificial joints and links can compete with the human skeleton. In contrast, the comparison of locomotion functions shows that robots are trailing behind in energy efficiency, operational time, and transportation costs. Robots are capable of obstacle negotiation, object manipulation, swimming, playing soccer, or vehicle operation. Despite the impressive advances of humanoid robots in the last two decades, current robots are not yet reaching the dexterity and versatility to cope with more complex manipulation and locomotion tasks (e.g., in confined spaces). We conclude that state-of-the-art humanoid robotics is far from matching the dexterity and versatility of human beings. Despite the outperforming technical structures, robot functions are inferior to human ones, even with tethered robots that could place heavy auxiliary components off-board. The persistent advances in robotics let us anticipate the diminishing of the gap.

General Image Manipulation Detection Using Feature Engineering and a Deep Feed-Forward Neural Network

Within digital forensics, a notable emphasis is placed on the detection of the application of fundamental image-editing operators, including but not limited to median filters, average filters, contrast enhancement, resampling, and various other operations closely associated with these techniques. When conducting a historical analysis of an image that has potentially undergone various modifications in the past, it is a logical initial approach to search for alterations made by fundamental operators. This paper presents the development of a deep-learning-based system designed for the purpose of detecting fundamental manipulation operations. The research involved training a multilayer perceptron using a feature set of 36 dimensions derived from the gray-level co-occurrence matrix, gray-level run-length matrix, and normalized streak area. The system detected median filtering, mean filtering, the introduction of additive white Gaussian noise, and the application of JPEG compression in digital Images. Our system, which utilizes a multilayer perceptron trained with a 36-feature set, achieved an accuracy of 99.46% and outperformed state-of-the-art deep-learning-based solutions, which achieved an accuracy of 97.89%.

Large-scale fabrication of conductive yarn with synergistic conductive coating for high-efficient strain sensing and photothermal conversion

With the rapid development of wearable electronics, conductive yarn strain sensors have attracted much attention due to their excellent flexibility, conformability, and knittability. However, it is still a great challenge to prepare flexible conductive yarn strain sensors with high sensitivity and wide working range simultaneously. Here, a large-scale fabrication of conductive spandex yarn (SY) with synergistic conductive coating composed of lower stable carbon nanotubes (CNTs)-polyaniline (PANi) hybrid layer and upper ultrasensitive cracked PANi layer was successfully achieved via the simple solvent swelling, non-solvent-induced phase separation (NIPS), and in-situ reduction processes. Thanks to the synergistic effect of the double layered conductive coating and its tunable microstructure based on the PANi content, the assembled conductive SY strain sensor exhibits wide working range (0–321 %), high sensitivity (GF is 43, 950, and 2439 for strain range of 0–100 %, 170–270 %, and 280–321 %, respectively), ultralow detection limit (0.5 %), fast response/recovery time (140 ms/160 ms), and excellent fatigue resistance (4000 cycles). As a proof of concept, the strain sensor can be used for wearable applications to achieve the effective detection of full-range human motion and physiologic signals. Besides, it also displays great potential in human-computer interaction for reliable operation of remote-control manipulator and flexible electronic textile for spatial pressure distribution identification. Finally, owing to the excellent optical absorbing ability of PANi and CNTs, the conductive SY exhibits high-efficient and stable photothermal conversion capacity even under the stretching and bending states, endowing it with good wearing comfort. This study provides a convenient but effective strategy for the fabrication of high-performance wearable strain sensor with excellent thermal management capacity.

Detecting Images in Two-Operator Series Manipulation: A Novel Approach Using Transposed Convolution and Information Fusion

Digital image forensics is a crucial emerging technique, as image editing tools can modify them easily. Most of the latest methods can determine whether a specific operator has edited an image. These methods are suitable for high-resolution uncompressed images. In practice, more than one operator is used to modify image contents repeatedly. In this paper, a reliable scheme using information fusion and deep network networks is presented to recognize manipulation operators and the operator’s series on two operators. A transposed convolutional layer improves the performance of low-resolution JPEG compressed images. In addition, a bottleneck technique is utilized to extend the number of transposed convolutional layers. One average pooling layer is employed to preserve the optimal information flow and evade the overfitting concern among the layers. Moreover, the presented scheme can detect two operator series with various factors without including them in training. The experimental outcomes of the suggested scheme are encouraging and better than the existing schemes due to the availability of sufficient statistical evidence.

Application of stereoscopic unequal S-plasty for reconstuction of the congenital hypoplastic ear lobe cleft associated with soft tissue deficiency

Objective: To explore the ideal way of using the stereoscopic unequal S-plasty in reconstruction of the congenital hypoplastic ear lobe cleft with soft tissue deficiency. Methods: Data of 10 patients with the congenital hypoplastic ear lobe cleft associated with soft tissue deficiency who were treated using the stereoscopic unequal S-plasty in the plastic cosmetic surgery of Xuzhou Central Hospital from Aug 2018 to Aug 2022 were retrospectively analyzed. Six patients were male, 4 were female. Their ages ranged from 6 years to 19 years old, with a mean age of 13 years. Lobe deficiency size ranged from 0.8 cm×0.5 cm to 1.2 cm×1.0 cm. Results: The post-operation flaps had no venous congestion, infection or necrosises. During 3 to 12 months of follow-up, the technique made the shape of the ear lobe smoother. The incisions left inconspicuous scars. The result was satisfactory in terms of matching the contralateral normal ear lobe in shape and symmetry. Doctors and patients were satisfied with the results. Conclusions: The stereoscopic unequal S-plasty is an effective way to correct the the severe congenital ear lobe deformity. The good result,simple manipulation and short operation time are the advantages of this method.

Компьютерное моделирование рекуперативного кривошипного механизма поворота колонны манипулятора лесовозного автопоезда

The study is aimed at improving the efficiency of the hydraulic manipulators of timber-carrying road trains operating in difficult natural and climatic conditions. The relevance of the scientific direction is substantiated, aimed at reducing energy losses in the hydraulic drives of manipulators in the process of performing loading and unloading operations. The works of foreign scientists are analyzed, which made it possible to identify promising areas for improving the efficiency of hydraulic manipulators, including the development of more modern drives, increasing productivity, accuracy and automation of their control processes. In order to improve the energy efficiency, performance and reliability of hydraulic manipulators of timber road trains, the authors proposed a promising design of the column slewing mechanism with a crank drive. The study was based on mathematical and simulation modeling, numerical methods, as well as modern methods for obtaining and processing information with computer support. A mathematical model and a computer program for the operation of a hydraulic manipulator with a regenerative crank drive of the column slewing mechanism made it possible to estimate the recuperated energy and the swing amplitude of the transported load. When using a hydraulic manipulator equipped with the proposed crank drive, the boom length of which is on average 6 m, and the weight of the transported timber is 600 kg, the amount of energy that can be stored in the pneumohydraulic accumulator is about 1300 J. The angular unevenness of the crank drive is 23.6 % and 4.6 % when assessed in terms of recuperated energy and load swing amplitude, respectively. For a typical hydraulic manipulator with a boom length of 6 m, when braking the rotation of the column, the recuperation system allows to store from 0.39 to 2.59 kW with a load mass of 200 to 1400 kg, respectively, with an acceptable load swing amplitude, respectively, from 0.2 to 0.48 m. The obtained results will be used as recommendations for the purpose of finalizing the proposed crank drive of the rotary device of the hydraulic manipulator at the stage of its design.

Conservative treatment of supination and external rotation for type Ⅲ and Ⅳankle fracture by bone setting

To explore curative effect of conservative treatment of supination-lateral rotation (SER) with type Ⅲ and Ⅳ ankle fracture by bone setting technique. From January 2017 to December 2019, 64 patients diagnosed with SER with type Ⅲ and Ⅳ ankle fracture were treated with manipulative reduction and conservative treatment (manipulation group) and surgical treatment with open reduction and internal fixation (operation group), 32 patients in each group. In manipulation group, there were 17 males and 15 females, aged from 15 to 79 years old with an average of (51.42±13.68) years old;according to Lauge-Hansen classification, there were 8 patients with supination external rotation type Ⅲ and 24 patients with type Ⅳ. In operation group, there were 13 males and 19 females, aged from 18 to 76 years old with an average of (47.36±15.02) years old;7 patients with type Ⅲ and 25 patients with type Ⅳ. Displacement of ankle fracture was measured by Digimizer software, and compared before treatment, 3 and 12 months after treatment between two groups. Lateral medial malleolus displacement, lateral medial malleolus displacement, lateral malleolus displacement, lateral malleolus displacement, lateral malleolus contraction displacement and posterior malleolus displacement were measured and compared between two groups. Mazur score was used to evaluate ankle joint function. All patients were followed up from 12 to 36 months with an average of (17.16±9.36) months. There were statistical differences in lateral medial malleolus displacement, lateral medial malleolus displacement, lateral malleolus displacement, lateral malleolus displacement, lateral malleolus contraction displacement and posterior malleolus displacement in manipulation group before and after reduction(P<0.05). Compared with operation group, there were no statistically significant differences in lateral malleolus shift, lateral malleolus shift, lateral malleolus contraction shift(P>0.05), while there were statistically significant differences in lateral malleolus shift, posterior malleolus shift up and down (P<0.05). Mazur scores of ankle joint at 3 months after treatment in manipulation group and operation group were 68.84±13.08 and 82.53±7.31, respectively, and had statistical differences(P<0.05), while there was no difference in evaluation of clnical effect(P>0.05). There were no differences in Mazur score and evaluation of clnical effect between two groups at 12 months after treatment (P>0.05). Bone setting technique could effectively correct lateral displacement of medial malleolus, lateral displacement of medial malleolus, lateral displacement of lateral malleolus and lateral contraction displacement of lateral malleolus in supination lateral rotation type Ⅲ and Ⅳ ankle fracture, and has good long-term clinical effect, which could avoid operation for some patients and restore ankle function after fracture.

An image-guided microfluidic system for single-cell lineage tracking.

Cell lineage tracking is a long-standing and unresolved problem in biology. Microfluidic technologies have the potential to address this problem, by virtue of their ability to manipulate and process single-cells in a rapid, controllable and efficient manner. Indeed, when coupled with traditional imaging approaches, microfluidic systems allow the experimentalist to follow single-cell divisions over time. Herein, we present a valve-based microfluidic system able to probe the decision-making processes of single-cells, by tracking their lineage over multiple generations. The system operates by trapping single-cells within growth chambers, allowing the trapped cells to grow and divide, isolating sister cells after a user-defined number of divisions and finally extracting them for downstream transcriptome analysis. The platform incorporates multiple cell manipulation operations, image processing-based automation for cell loading and growth monitoring, reagent addition and device washing. To demonstrate the efficacy of the microfluidic workflow, 6C2 (chicken erythroleukemia) and T2EC (primary chicken erythrocytic progenitors) cells are tracked inside the microfluidic device over two generations, with a cell viability rate in excess of 90%. Sister cells are successfully isolated after division and extracted within a 500 nL volume, which was demonstrated to be compatible with downstream single-cell RNA sequencing analysis.

A 94.1 g scissors-type dual-arm cooperative manipulator for plant sampling by an ornithopter using a vision detection system

AbstractThe sampling and monitoring of nature have become an important subject due to the rapid loss of green areas. This work proposes a possible solution for a sampling method of the leaves using an ornithopter robot equipped with an onboard 94.1 g dual-arm cooperative manipulator. One hand of the robot is a scissors-type arm and the other one is a gripper to perform the collection, approximately similar to an operation by human fingers. In the move toward autonomy, a stereo camera has been added to the ornithopter to provide visual feedback for the stem, which reports the position of the cutting and grasping. The position of the stem is detected by a stereo vision processing system and the inverse kinematics of the dual-arm commands both gripper and scissors to the right position. Those trajectories are smooth and avoid any damage to the actuators. The real-time execution of the vision algorithm takes place in the lightweight main processor of the ornithopter which sends the estimated stem localization to a microcontroller board that controls the arms. The experimental results both indoors and outdoors confirmed the feasibility of this sampling method. The operation of the dual-arm manipulator is done after the perching of the system on a stem. The topic of perching has been presented in previous works and here we focus on the sampling procedure and vision/manipulator design. The flight experimentation also approves the weight of the dual-arm system for installation on the flapping-wing flying robot.

A Review of Optical Tweezers with Metasurfaces

Optical tweezers (OTs) have made significant progress in recent years, realizing the non-contact optical manipulation of target objects through the interaction between light and matter. In addition to trapping particles with the intensity gradient of the beam, a series of complex optical elements are required to properly modulate the beams to expand the operation of optical manipulation. The development of metasurfaces alleviates this problem. Due to the merits of miniaturization, planarization, multi-function, and integration of metasurfaces, these kinds of novel devices have been applied in OT systems. Metasurface devices have been used to replace traditional objective lenses, achieving device integration and even obtaining multi-function of OTs with unique optical properties in applications. OTs with metasurfaces have developed rapidly, and a great deal of work has been carried out on OTs with metasurfaces, as well as discussions on their practical applications. In this review, we regard the latest progress in the field of OTs with metasurfaces. We classify OTs with metasurface and summarize the new impetus brought by metasurfaces for the development of OTs.

Lung cancer subtyping from gene expression data using general and enhanced Fuzzy min–max neural networks

AbstractIn this article, we address the problem of lung cancer diagnosis from gene expression data, which is now recognized as an effective means for early treatment and prevention of cancer. Specifically, we employ Fuzzy min–max (FMM) classifier for the task which is a well‐known neuro‐fuzzy neural network. The idea is to take advantage of the fuzzy class definitions whose boundaries are set using the min–max hyperbox constructed for each class. We implement two advanced FMM neural network architectures: general Fuzzy min–max (GFMM) and enhanced Fuzzy min–max (EFMM) for the classification of lung cancer subtypes from gene expression data. The advantage of GFMM is that it involves very simple operations for hyperbox manipulation, and can handle both labeled and unlabeled data. On the other hand, EFMM proposes three heuristic rules related to hyperbox expansion, contraction and the overlap test, which enhances the learning algorithm. We perform the classification of gene expression data using these two models, and then we analyze the performance by visualizing the hyperboxes obtained after training, and compare the accuracies of these classifiers with the state of the art. Least absolute shrinkage and selection operator (LASSO) is used for selecting the informative genes from the high‐dimensional gene expression data. From the empirical results, we observe that GFMM with LASSO gives the best performance of all, with validation accuracy of 98.04% and cross‐validation accuracy of 94.06%.

Machine learning based multipurpose medical image watermarking.

Digital data security has become an exigent area of research due to a huge amount of data availability at present time. Some of the fields like medical imaging and medical data sharing over communication platforms require high security against counterfeit access, manipulation and other processing operations. It is essential because the changed/manipulated data may lead to erroneous judgment by medical experts and can negatively influence the human's heath. This work offers a blind and robust medical image watermarking framework using deep neural network to provide effective security solutions for medical images. During watermarking, the region of interest (ROI) data of the original image is preserved by employing the LZW (Lampel-Ziv-Welch) compression algorithm. Subsequently the robust watermark is inserted into the original image using IWT (integer wavelet transform) based embedding approach. Next, the SHA-256 algorithm-based hash keys are generated for ROI and RONI (region of non-interest) regions. The fragile watermark is then prepared by ROI recovery data and the hash keys. Further, the LSB replacement-based insertion mechanism is utilized to embed the fragile watermark into RONI embedding region of robust watermarked image. A deep neural network-based framework is used to perform robust watermark extraction for efficient results with less computational time. Simulation results verify that the scheme has significant imperceptibility, efficient robust watermark extraction, correct authentication and completely reversible nature for ROI recovery. The relative investigation with existing schemes confirms the dominance of the proposed work over already existing work.

Design and calibration of spoke piezoelectric six-dimensional force/torque sensor for space manipulator

The large manipulator outside the space cabin is a multi-degree of freedom actuator for space operations. In order to realize the automatic control and flexible operation of the space manipulator, a novel spoke structure piezoelectric six-dimensional force/torque sensor with redundancy ability, high stiffness and good decoupling performance is innovatively proposed. Based on the deformation coordination relationship, the redundancy measurement mechanism is revealed. The mathematical models of the sensor with and without branch fault are established respectively. The finite element model is established to verify the feasibility of structure and redundancy measuring principle of the sensor. Depending on the theoretical analysis and simulation analysis, the prototype of the sensor is developed. Static and dynamic calibration experiments are carried out. The actual output voltage signal of the six-dimensional force/torque sensor is collected to establish the equation between the standard input applied load and the actual output voltage signal. Based on ant colony optimized BP algorithm, performance indexes of the sensor with and without branch fault are analyzed respectively. The experimental results show that the spoke piezoelectric six-dimensional force/torque sensor with the eight-point support structure has good accuracy and reliability. Meanwhile, it has strong decoupling characteristic that can effectively shield the coupling between dimensions. The nonlinear errors and maximum interference errors of decoupled data with and without branch faults are less than 1% and 2%, respectively. The natural frequency of the six-dimensional force sensor can reach 2856.45 Hz and has good dynamic characteristics. The research content lays a theoretical and experimental foundation for the design, development and application of the new six-dimensional force/torque sensors with redundancy. Meanwhile, it will significantly improve the research level in this field, and provide a strong guarantee for the smooth implementation of force feedback control of the space station manipulator project.

Learning positioning policies for mobile manipulation operations with deep reinforcement learning

This work focuses on the operation of picking an object on a table with a mobile manipulator. We use deep reinforcement learning (DRL) to learn a positioning policy for the robot’s base by considering the reachability constraints of the arm. This work extends our first proof-of-concept with the ultimate goal of validating the method on a real robot. Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm is used to model the base controller, and is optimised using the feedback from the MoveIt! based arm planner. The idea is to encourage the base controller to position itself in areas where the arm reaches the object. Following a simulation-to-reality approach, first we create a realistic simulation of the robotic environment in Unity, and integrate it in Robot Operating System (ROS). The drivers for both the base and the arm are also implemented. The DRL-based agent is trained in simulation and, both the robot and target poses are randomised to make the learnt base controller robust to uncertainties. We propose a task-specific setup for TD3, which includes state/action spaces, reward function and neural architectures. We compare the proposed method with the baseline work and show that the combination of TD3 and the proposed setup leads to a 11% higher success rate than with the baseline, with an overall success rate of 97%. Finally, the learnt agent is deployed and validated in the real robotic system where we obtain a promising success rate of 75%.

Coordinated inauthentic behavior: An innovative manipulation tactic to amplify COVID-19 anti-vaccine communication outreach via social media.

Coordinated inauthentic behavior (CIB) is a manipulative communication tactic that uses a mix of authentic, fake, and duplicated social media accounts to operate as an adversarial network (AN) across multiple social media platforms. The article aims to clarify how CIB's emerging communication tactic "secretly" exploits technology to massively harass, harm, or mislead the online debate around crucial issues for society, like the COVID-19 vaccination. CIB's manipulative operations could be one of the greatest threats to freedom of expression and democracy in our society. CIB campaigns mislead others by acting with pre-arranged exceptional similarity and "secret" operations. Previous theoretical frameworks failed to evaluate the role of CIB on vaccination attitudes and behavior. In light of recent international and interdisciplinary CIB research, this study critically analyzes the case of a COVID-19 anti-vaccine adversarial network removed from Meta at the end of 2021 for brigading. A violent and harmful attempt to tactically manipulate the COVID-19 vaccine debate in Italy, France, and Germany. The following focal issues are discussed: (1) CIB manipulative operations, (2) their extensions, and (3) challenges in CIB's identification. The article shows that CIB acts in three domains: (i) structuring inauthentic online communities, (ii) exploiting social media technology, and (iii) deceiving algorithms to extend communication outreach to unaware social media users, a matter of concern for the general audience of CIB-illiterates. Upcoming threats, open issues, and future research directions are discussed.

Large Torsion Thin Artificial Muscles Tensegrity Structure for Twist Manipulation

Tensegrity structures have been actively studied in recent years because they are lightweight, compliant, and flexible, which are properties not typically found in conventional robots. This structure can be modularized to create soft robots that operate in unknown environments such as cave or space with more complex and effective behavior. The basic deformation elements in modularization are stretching, bending, and torsion. Among them, torsional motion is important for proper manipulation and rotational operation. However, active, and large torsion in soft tensegrity structures has not been developed. Therefore, this study describes torsional deformation and a novel arrangement method for thin artificial muscles. The proposed method leads to the optimal placement of artificial muscles for torsion, by which we generated a large torsion of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 50 deg. This is more than 2.5 times larger than that of a previous tensegrity without compromising the favorable properties of the structure. Furthermore, by modularizing the tensegrity structure, a tensegrity arm capable of removing a plastic bottle cap was developed. The applicability of torsional deformation and the usefulness of modularization of the structure are demonstrated.

Nonlinear effects in a Floquet-driven optomechanical system

We investigate theoretically the nonlinear effects in a Floquet-driven optomechanical system with quadratic coupling. When the periodically modulated driving field is strong, we establish an effective time-dependent model to describe this system. Using the Keldysh approach, we calculate the retarded Green's function to study the response behavior of the system to external probing. We find that when the $n\mathrm{th}$ sideband of a probe field satisfies the condition of two-phonon resonance, the transparency window occurs. In addition, we find some abnormal behaviors of the output field, which have no counterpart in the standard optomechanical models. These results provide a promising platform for controlling light propagation and light manipulation operations which have potential applications in quantum precision measurement techniques.

Analysis of a heat dissipation scheme for a space manipulator joint

A space manipulator is an important tool that assists humans in space exploration. The thermal control of the joint is important to the normal operation of the space manipulator. This paper proposes an effective scheme for the thermal design of a space manipulator in view of thermal characteristics of the manipulator joint, such as the harsh external thermal environment, complex flight attitude and large internal power dissipation. The adaptability of the size of the radiating surface under various extreme operating conditions is compared and analyzed. The results show that in extreme high- and low-temperature running modes, when the radiating surface has dimensions of 100 mm × 120 mm, the temperature of each component obtained by NX/TMG and a heat balance test meets thermal requirements. Additionally, the simulation results of the joint shell and electricity box differ from the experimental results within 4.2 °C. The dimensions of the radiating surface are thus designed as 100 mm × 120 mm, which well meets the needs of thermal control. The present study thus provides a theoretical basis for improving the reliability and thermal optimization of manipulator joints.

Effects of manipulator operation task and troubleshooting task on blood pressure indexes of oceanauts

Objective: To explore the characteristics and rules of blood pressure changes in oceanauts during simulated operation of manipulator and troubleshooting tasks with different difficulty. Methods: In July 2020, 8 deep-sea manned submersible oceanauts, 6 males and 2 females, were selected as objects. In the 1∶1 model of Jiaolong deep-sea manned submersible, the oceanauts performed manipulator operation tasks and troubleshooting tasks with different difficulties, measured the continuous blood pressure of the oceanauts, filled in the NASA Task Load Index (NASA-TLX scale) after the completion of a single mission, and the changes of systolic pressure (SBP), diastolic pressure (DBP), mean arterial pressure (MAP) and mental workload were analyzed. Results: In a single task, the SBP, DBP and MAP of the oceanauts increased first and then decreased. The blood pressure values at the third minute were significantly lower than those at the first minute (P<0.01), and those at the fifth minute were significantly higher than those at the third minute (P<0.01). When performing the same task, compared with the quiet state, SBP, DBP and MAP increased when the oceanauts performed low difficulty, high difficulty, high difficulty+2-back manipulator operation task and troubleshooting task (P<0.05). When the task difficulty was the same, the SBP and MAP of oceanauts performing manipulator operation tasks were higher than those of oceanauts performing troubleshooting tasks (P<0.05). Compared with low difficulty tasks, the scores of NASA-TLX scale for oceanauts performing high difficulty manipulator operationtasks were significantly higher (P<0.05). Compared with the low difficulty task and high difficulty task, the scale score of the high difficulty+2-back troubleshooting task was significantly higher (P<0.05). When the task difficulty was the same, the scale scores of low difficulty and high difficulty manipulator operation tasks were significantly higher than those of troubleshooting tasks (P<0.05). SBP, DBP, MAP of No. 1, No. 3, No. 4, No. 5, and No. 7 oceanauts (all of whom had 6 years of diving) were positively correlated with NASA-TLX scale scores (r>0.8, P<0.05) . Conclusion: In the process of manned deep-sea diving, when the oceanauts perform manipulator operation tasks and troubleshooting tasks, with the increase of task difficulty, the mental load of oceanauts increases, and the blood pressure index increases significantly in a short time. At the same time, improving the proficiency of operation can reduce the variation range of blood pressure indexes. Blood pressure can be used as an effective reference to evaluate the difficulty of operation and guide scientific training.

Path planning algorithm of dual arm space intelligent robot

In order to solve the cooperation problem between the two arms of the dual arm robot, improve the effect and accuracy of the path planning of the intelligent robot, in this study, a new path planning algorithm for dual arm space (DAS) intelligent robot is designed. By analyzing the kinematics performance of DAS intelligent robot, the operation law of DAS intelligent robot is determined. By analyzing the collision that needs to be considered during the operation of DAS intelligent manipulator, a collision detection method based on capsule envelope is proposed to detect the collision of obstacles in the running path. Finally, the path planning model of DAS intelligent robot is designed by using immune genetic algorithm. The experimental results show that the path planned by this method can avoid obstacles and dangerous areas, and the accuracy of path planning for the existing environment is always higher than 90%. With the increase of iteration times, the planning time is relatively stable, about 5.5 seconds. The proposed method can enhance the effect and accuracy of path planning, effectively shorten the time of path planning, and improve the work efficiency of DAS intelligent robot.