Manipulation Problem Research Articles

Манипуляция как феномен информационного общества

The article touches upon the most urgent problem of information manipulation with the aim of influencing society. In most sources manipulation is interpreted as the use of certain techniques and technologies, under the influence of which the behavior of people changes in the direction necessary for the manipulator. It is noted that the most favorable conditions for the implementation of manipulation technologies are formed in the information society, in which information, knowledge and information technologies play a special role. The analysis of existing theories allows us to consider the information society as a special type of society at the post-industrial stage of development, the production of which is based on information. Various algorithms for presenting information are used, from the elementary dissemination of information that cannot be verified to its purposeful combination, taking into account the peculiarities of perception by different audiences, including the specifics of the preferable communication channels. At different stages society development manipulation has its own characteristics. In today's information society, the biggest threat is the media. The media today is a real force in society, which, with the help of information messages, forms certain social attitudes and influences the change in a person's beliefs. The process of manipulation includes the imposition of a certain social stereotypes, thanks to which an individual reproduces the necessary behavior patterns, perception and thinking changes. The results of a number of sociological studies reveal the features of impact technologies, among which the authors note the special role of the media in imposing stereotypes through the creation of socially significant images, which also act as propaganda and agitation tools.

Inverse Kinematics of an Anthropomorphic 6R Robot Manipulator Based on a Simple Geometric Approach for Embedded Systems

This manuscript presents an efficient algorithm for solving the inverse kinematics problem of a 6R robot manipulator to be deployed on embedded control hardware. The proposed method utilizes the geometric relationship between the end-effector and the base of the manipulator, resulting in a computationally efficient solution. The approach aims to minimize computational complexity and memory consumption while maintaining the accuracy and real-time performance demonstrated by simulations and verified by experimental results on an embedded system. Furthermore, the manipulator is analyzed in terms of singularities, limits, the workspace, and general solvability. Due to the simplicity of the algorithm, a platform-independent implementation is possible. As a result, the average calculation time is reduced by a factor of five to eight and the average error is decreased by a factor of fifty compared to a powerful analytical solver.

Implicit contact-rich manipulation planning for a manipulator with insufficient payload

Purpose This paper aims to study using a mobile manipulator with a collaborative robotic arm component to manipulate objects beyond the robot’s maximum payload. Design/methodology/approach This paper proposes a single-short probabilistic roadmap-based method to plan and optimize manipulation motion with environment support. The method uses an expanded object mesh model to examine contact and randomly explores object motion while keeping contact and securing affordable grasping force. It generates robotic motion trajectories after obtaining object motion using an optimization-based algorithm. With the proposed method’s help, the authors plan contact-rich manipulation without particularly analyzing an object’s contact modes and their transitions. The planner and optimizer determine them automatically. Findings The authors conducted experiments and analyses using simulations and real-world executions to examine the method’s performance. The method successfully found manipulation motion that met contact, force and kinematic constraints. It allowed a mobile manipulator to move heavy objects while leveraging supporting forces from environmental obstacles. Originality/value This paper presents an automatic approach for solving contact-rich heavy object manipulation problems. Unlike previous methods, the new approach does not need to explicitly analyze contact states and build contact transition graphs, thus providing a new view for robotic grasp-less manipulation, nonprehensile manipulation, manipulation with contact, etc.

Adaptive Prescribed Performance Control of Unmanned Aerial Manipulator With Disturbances

This article presents the problem of autonomous control of an unmanned aerial manipulator (UAM) developed for operation with unknown disturbances, wherein the disturbances from the coupling effect between the UAM and the external environment need to be considered. Regarding the coupling force as a disturbance to the entire UAM system, an adaptive prescribed performance control (APPC) scheme utilizing the knowledge of prescribed performance is proposed to guarantee the transient and steady-state performance responses. Also, an adaptive law is designed to estimate the upper boundary parameters of the UAM system uncertainties and disturbances, wherein the restrictive constant boundary assumptions and the prior information of the upper bound are not required in the controller design. Furthermore, to enable safe manipulation in a realistic situation, an end-effector trajectory generation method is presented satisfying the joint angle limitation. For the validation of the proposed method, the simulation results of numerical simulation comparisons are shown. Moreover, experimental scenarios including stable flight and simulated co-work with humans in complex environments are designed to verify the proposed method. <i>Note to Practitioners</i>&#x2014;This article is motivated by the problem of aerial manipulation under unknown disturbances, which may be caused by the wide movement of the manipulator and the sudden loading or unloading of an object. Existing approaches for aerial manipulation often require the assumption of a constant or slowly varying external disturbance. However, a priori bounded disturbance might impose a priori bound on the system state before obtaining closed-loop stability. In this article, the proposed controller with an adaptive law is designed to estimate the upper boundary parameters of the overall disturbances and ensure the predefined performance, so that the prior information of the upper bound of disturbances is not required. The performance of the proposed control strategy is demonstrated via numerical simulation comparisons and experiments, including stale flight and simulated co-work with humans in a complex environment.

ПСИХОЛОГІЯ ВИКОРИСТАННЯ СОЦІАЛЬНИХ ІНТЕРНЕТ МЕРЕЖ СУЧАСНИМИ УКРАЇНСЬКИМИ КОРИСТУВАЧАМИ

The article describes the peculiarities of using modern Internet networks and their psychological impact on the psychological well-being of Ukrainian users. On average, a modern person who owns a computer or smartphone spends on social networks from several minutes to several hours. The scale of humanity's involvement in social networks does not allow us to consider this activity as something insignificant. It is quite obvious that social networks are becoming the most important social phenomenon and influence society and an individual. The most frequently expressed concerns concern the impact of modern networks on users' psychological well-being (self-esteem, emotions, social interactions) and their mental health (anxiety, depression, loneliness, addiction). In this small review, we set out to consider the existing research evidence, dedicated to this problem and expand their research on this topic. As for attempts to independently escape from the embrace of the social network, users themselves sometimes evaluate these actions as "self-sacrifice" or "detoxification", i.e. quite clearly draw parallels between chemical addictions and Internet content addiction. On the other hand, it is assumed that social interaction in the network can improve psychological well-being, for example, through self-presentation or through establishing contacts with like-minded people, etc. It was established that the interviewees cannot monitor their own well-being and experience difficulties in describing their well-being after being in a social network. Subjects are internalized into virtual life, more than they realize. They prefer to write a message than to call in person. They communicate less with real friends, they prefer virtual communication. Text messages (emoticons, memes) are used more for communication. They choose entertainment content and consume news from social networks. A high level of trust in the information that users consume from social networks is revealed, it is worth noting that the respondents do not check this information for reliability. Therefore, there is a problem of propaganda and manipulation on the mass consciousness of people, this problem requires a more detailed study in further research. Respondents spend more free time on social networks than they wanted. Women are more dependent on social networks. Young women are guided by fashion, values and standards that they consume from social networks and prefer online dating. They do not prefer new virtual acquaintances, more older men and women are wary of virtual strangers. The questions that arise are reduced to the following: can it be argued that excessive activity in the social network reflects depressive tendencies of users; how social networks affect self-esteem and psychological well-being; to what extent social networks can become an object of addiction, by analogy with the well-known Internet addiction. All these features in one way or another affect the feeling of psychological well-being of an individual, so further research requires a detailed study of the influence of social Internet networks on the psychological well-being of an individual.

Prescribed Fixed-Time Adaptive Neural Control for Manipulators with Uncertain Dynamics and Actuator Failures

In this paper, a fixed-time adaptive neural control scheme is proposed to solve the prescribed tracking problem of robot manipulators in the presence of uncertain dynamics, and stuck-type actuator failures which are unknown in time, pattern, and values. Technically, the combination of neural networks and adaptive control is used to handle the uncertainties in system dynamics, an adaptive compensation mechanism is designed to accommodate the failures occurring in actuators, and also a systematic design procedure based on the prescribed performance bounds is presented to establish the conditional inequality for ensuring fixed-time stability. With our scheme, it can be proved rigorously that the tracking errors in joint space can always be kept within the prescribed bounds, and converge to a small region of zero in a bounded settling time, in addition to the closed-loop signal boundedness. The proposed scheme is validated through simulations.

Application of the M-Score Model to Test the Reliability of Financial Statements at Companies Listed on the Vietnamese Stock Market

The reliability of financial statements is important to many people such as investors, corporate shareholders, and auditors. A reliable financial report is free from problems of fraud and manipulation by corporate management. Using the methodology and meta-analysis, the research team found that the application of the M-score model in Vietnam is not yet popular. The number of research papers on the M-score model is small and there is no research using this model to assess the reliability of financial statements. Research results with actual data from the unaudited financial statements of a typical enterprise show that the application of the M-score model to assess the reliability or detect fraud of financial statements is an appropriate fit. However, the research team also found that the M-score model also has a high probability of incorrect identification of unreliable financial statements. Therefore, from the research results, we recommend that investors, shareholders, and stakeholders use a combination of the M-score model together with other technical analysis tools to be able to identify whether a financial statement is reliable.

Target-Free Text-Guided Image Manipulation

We tackle the problem of target-free text-guided image manipulation, which requires one to modify the input reference image based on the given text instruction, while no ground truth target image is observed during training. To address this challenging task, we propose a Cyclic-Manipulation GAN (cManiGAN) in this paper, which is able to realize where and how to edit the image regions of interest. Specifically, the image editor in cManiGAN learns to identify and complete the input image, while cross-modal interpreter and reasoner are deployed to verify the semantic correctness of the output image based on the input instruction. While the former utilizes factual/counterfactual description learning for authenticating the image semantics, the latter predicts the "undo" instruction and provides pixel-level supervision for the training of cManiGAN. With the above operational cycle-consistency, our cManiGAN can be trained in the above weakly supervised setting. We conduct extensive experiments on the datasets of CLEVR and COCO datasets, and the effectiveness and generalizability of our proposed method can be successfully verified. Project page: sites.google.com/view/wancyuanfan/projects/cmanigan.

Detecting review manipulation from behavior deviation: A deep learning approach

This research considers the problem of review manipulation by exploring rating distribution deviations and proposing a detection framework that captures review bias. We characterize the severity of review manipulation based on the degree to which the corresponding rating deviates from a normal distribution. Then we utilize deep learning approaches to learn hidden textual representations of unmanipulated reviews for biased review detection. Experiments conducted on 1,396,132 movie reviews demonstrate that highly/low biased reviews yield significant difference through our proposed model. Moreover, sentiment and topic analysis on experimental results reveal that biased reviews differentiate from authentic reviews in covering less movie-related topics and embedding stronger and more inflammatory emotions. The findings provide managerial insights for business owners in detecting review manipulation and suggest practical signals for online consumers to distinguish misleading information online.

A clever trilayer assembly strategy for 2D materials

Recently in Matter, Hu et al. developed a trilayer structure composed of 2D materials, intermediate layer, and substrate, which enabled decoupling of the mono-mode instabilities and designable deterministic mode toward self-assembly of atomically thin 2D materials. The strategy is universal for different 2D materials and induces anisotropic piezoresistive and mechanical-optoelectrical coupling effects, being utilized for fabrication of highly sensitive and ultra-fast responsive mechanical sensors. Recently in Matter, Hu et al. developed a trilayer structure composed of 2D materials, intermediate layer, and substrate, which enabled decoupling of the mono-mode instabilities and designable deterministic mode toward self-assembly of atomically thin 2D materials. The strategy is universal for different 2D materials and induces anisotropic piezoresistive and mechanical-optoelectrical coupling effects, being utilized for fabrication of highly sensitive and ultra-fast responsive mechanical sensors. Deterministically self-assembled 2D materials and electronicsHu et al.MatterApril 10, 2023In BriefMode-decoupled instability-driven deterministic self-assemblies, including deterministic mode, scale, direction, and dynamic self-assembly, of atomically thin 2D nanocrystals are achieved by overcoming the key problem of mechanical instability mode manipulation from randomness to determinism. The deterministic self-assemblies endow unique properties distinct from those of their parent 2D materials, such as anisotropic piezoresistive effects. Benefited from the properties induced by deterministic self-assemblies, we report a concept of deterministically self-assembled micro/nano-electronics of 2D materials, such as 3D anisotropic tactile sensors. Full-Text PDF

Obstacle Avoidance Path Planning of 7-DOF Redundant Manipulator Based on Improved Ant Colony Optimization

Background: Obstacle avoidance path planning is an important parameter of robot manipulators. Path planning can directly affect the working efficiency of the manipulator. Objective: This study aims to summarize the optimization design method from a large number of literature and propose a new optimization design method to make the planned obstacle avoidance path of the manipulator shorter and smoother. Methods: The forward and inverse kinematics of the redundant manipulator is solved. Secondly, the obstacle and the robot manipulator envelope are simplified for collision detection. Then, the ant colony algorithm is improved by adding an obstacle environment to the construction of the heuristic function and dynamically adjusting the heuristic function factor to make the shortest path distance planned by the algorithm. Finally, the worst ant colony is added to the pheromone update to avoid the algorithm falling into the local optimal solution. Results: Through experiments and comparative studies, the optimized design process shows that the path planned by the improved ant colony algorithm has obvious advantages of shorter path distance and smoother path distance, which verifies the rationality of the improved algorithm. Conclusion: This method optimizes the convergence speed of the ant colony algorithm and avoids the ant colony algorithm from falling into the local optimal solution, which is of great significance for improving the obstacle avoidance path planning problem of a redundant manipulator with a degree of freedom.

An HQP-Based Obstacle Avoidance Control Scheme for Redundant Mobile Manipulators Under Multiple Constraints

It is a challenging problem for redundant wheeled mobile manipulators to satisfy multiple physical constraints and avoid obstacles while performing certain tasks, not to mention constraining tracking performance. In this paper, a control scheme based on hierarchical quadratic programming-prescribed performance control (HQP-PPC) is proposed. The first layer of HQP can achieve trajectory tracking, obstacle avoidance and physical constraints. The second layer of HQP is used to guide the direction of obstacle avoidance and produce a smoother planned path. The prescribed performance function (PPF) can ensure tracking performance so that the physical constraints and obstacle avoidance constraints are satisfied in actual motion. Moreover, the proposed controller can guarantee the tracking performance of the end effector due to the characteristics of PPF. Finally, the effectiveness and superiority of the proposed method are verified by simulations and experiments.

Integrated planning and control of robotic surgical instruments for task autonomy

Agile maneuvers are essential for robot-enabled complex tasks such as surgical procedures. Prior explorations on surgery autonomy are limited to feasibility study of completing a single task without systematically addressing generic manipulation safety across different tasks. We present an integrated planning and control framework for 6-DoF robotic instruments for pipeline automation of surgical tasks. We leverage the geometry of a robotic instrument and propose the nodal state space to represent the robot state in SE (3) space. Each elementary robot motion could be encoded by regulation of the state parameters via a dynamical system. This theoretically ensures that every in-process trajectory is globally feasible and stably reached to an admissible target, and the controller is of closed-form without computing 6-DoF inverse kinematics. Then, to plan the motion steps reliably, we propose an interactive (instant) goal state of the robot that transforms manipulation planning through desired path constraints into a goal-varying manipulation (GVM) problem. We detail how GVM could adaptively and smoothly plan the procedure (could proceed or rewind the process as needed) based on on-the-fly situations under dynamic or disturbed environment. Finally, we extend the above policy to characterize complete pipelines of various surgical tasks. Simulations show that our framework could smoothly solve twisted maneuvers while avoiding collisions. Physical experiments using the da Vinci Research Kit validates the capability of automating individual tasks including tissue debridement, dissection, and wound suturing. The results confirm good task-level consistency and reliability compared to state-of-the-art automation algorithms.

Error feedback method (EFM) based dimension synthesis optimisation for four-bar linkage mechanism

In this study, we propose an error-feedback method (EFM) for constraint handling of the path-generation problem, which replaces the traditional penalty-functional method. Moreover, it proportionally redistributes solutions that do not satisfy the constraint conditions, such that each offspring can effectively participate in the iterative process and avoid additional computing resource wastage. To test the performance, the EFM, penalty, and self-adaptive–penalty-functional methods were applied to heuristic algorithms, such as the differential evolution (DE), teaching learning-based optimisation (TLBO), whale optimisation algorithm (WOA), and gaining–sharing knowledge (GSK). Three four-bar mechanisms of dimensional synthesis and one path-generation problem of a pickup manipulator was considered as examples. The numerical results showed that the algorithm processed by the new constraint-processing method exhibited improved performance compared to other methods.

Influence of spoken language in English-Speaking political media discourse

A great deal of attention is paid to the problems of political discourse because political discourse is the most frequently used event in society. The impact of speech on political discourse is discussed within the framework of political linguistics, pragmatic linguistics, discourse theory and psychology. The relevance of the topic of this article is due to the increased interest in the problem of manipulation of public opinion. As E. Siegel points out one of the clear manifestations of power is the monopoly on information and the right to speak. The ability of language to shape the worldview of the public plays a big role in the mentioned case. In this regard, one of the characteristic features of research in the field of political communication is that language is perceived as a means of achieving a pragmatic goal: to manipulate the addressee's cognition. Thus, we can talk about the strategy of manipulation. The great role of metaphors is noteworthy here. This article is devoted to the impact of speech with a metaphor, the source of which is the sports concept "loser". This metaphorical unit has a negative connotation and contains a strong emotional signal.

Adaptive sliding mode security control of wheeled mobile manipulators with Markov switching joints against adversarial attacks

This paper deals with the security control problem of a wheeled mobile manipulator that is subjected to various challenges, such as Markov switching parameters, actuator false data injection attacks, un-modeled nonlinearities, and deficient transition rates. As actuator attacks are often not fully known or predictable, an adaptive scheme is proposed to dynamically eliminate their negative effects. To achieve an ideal sliding motion, a smooth integral hyperplane is introduced. Since the transition rates of the joints may vary, it is important to design a controller that can maintain the expected sliding motion under different mode information. Additionally, stochastic stability analysis is conducted for the sliding motion considering different types of transition rates. Finally, simulation results are provided to demonstrate the effectiveness of the proposed method.

Development and Experimental Studies of a Method Based on a Reference Control Signal Generating System for Redundant Serial Manipulators

The paper presents the design and experimental study of a synthesis method based on reference signal generation systems. The method can be used for all actuators of redundant manipulators. The aforementioned systems aim to save the dynamic control accuracy of the working tools of serial manipulators when they move along arbitrary spatial trajectories, taking into account restrictions in all degrees of freedom and special cases of their link positions. The maintenance of the control accuracy could be ensured by eliminating the reach of all degrees of freedom of manipulators to their limits and to indicated special positions, characterized by an ambiguity when solving the inverse kinematic problems of various serial manipulators. This is in addition to preventing the reach of their working tools to the boundaries of the working area due to the use of a redundant degree of freedom when approaching the indicated undesirable positions. The experimental studies performed in this paper confirm the efficiency of the proposed method and allow accurate characteristics to be obtained.

A Review and Comparative Study of Differential Evolution Algorithms in Solving Inverse Kinematics of Mobile Manipulator

Mobile manipulator robots have become important pieces of equipment due to the high mobility of mobile subsystems and the high flexibility of manipulator subsystems. Considering the increasing degrees of freedom and the need to avoid singular locations, one of the most challenging problems is solving the inverse kinematics problem of mobile manipulator robots (IKMM). Of all the popular optimization algorithms, the differential evolution (DE) algorithm is the most effective method for quickly solving the IKMM problem with sufficient solutions. Currently, many strategies have been proposed for DE algorithms to improve the performance of solving mathematical problems; some symmetry strategies or symmetry functions have been introduced to DE algorithms. However, the effects of various DE algorithms on solving the actual IKMM lack a comprehensive explanation. Therefore, we divide various DE algorithms into three categories considering the control parameter selection and compare the specific optimization of various DE algorithms. Then, we compare the performance of various DE algorithms when solving the inverse kinematics problems of mobile manipulators with different degrees of freedom. Considering the effectiveness and the speed of the DE algorithm on the IKMM problem, we determine the best DE algorithm by comparing the error and time required to reach 100 random mission points and tracking the typical trajectories. Finally, the best-performing DE method is further improved by studying the selection of fundamental parameters in the best DE algorithm. Valuable conclusions are obtained from these experimental simulations, which can help with choosing an algorithm that is suitable for solving the inverse kinematics problem of mobile manipulator robots in practice.

Dual-Arm Mobile Manipulation Planning of a Long Deformable Object in Industrial Installation

In this letter, we present a planning method considering regrasp and mobility for the manipulation problem of a long deformable object in an industrial scenario. The object is carried through designated rollers by a dual-arm robot in the presence of environmental constraints. The problem is formulated by modeling the deformable object as a set of line segments and categorizing obstacles into different types. A hierarchical 2.5D manipulation planner is proposed, which first plans the ideal path of a deformable object in a 2D plane and obtains its topological representation. Next, dual-arm regrasps are determined by utilizing the deformation models, and collision-free paths are planned to meet topological constraints for the grippers. The feasibility of the proposed method is experimentally validated using a humanoid robot, by integrating the planner with a loco-manipulation planning framework and QP-based whole-body motion controller.

A General Stable Control Method for R-Type Underactuated Robot with Three Different Initial Situations

In this paper, we propose a general control method via the intelligent algorithm for a planar R-type underactuated robot. This control method solves the unified control problem of R-type underactuated manipulator. Meanwhile, the proposed method is also applicable to cases of nonzero initial velocity and interference rejection. Our total control program includes two stages. In the first stage, we design the trajectory based on the states of the actuated link, and then the controller is designed to track the planned trajectory to realize the objective of the actuated link. In the second stage, the trajectory with adjustable parameters is planned for the actuated link. Then, the adjustable parameters are calculated by the intelligent algorithm based on the underactuated constraints. Subsequently, the controller is designed to track the second trajectory to realize the objective of the actuated manipulator and the underactuated manipulator. Finally, the performance of the proposed method is verified through simulations.