Space Manipulator Research Articles

The Use of White Space in Poems: Meaning and Affect Making Through Manipulation of Space in Contemporary Indian Poetry

In poetry, line-breaks “shape meaning.” Poets use them to “encourage the interpretations they desire.” While several and often overlapping reasons may undergird the choice of a particular line-break in a poem, including “speed, sound, syntax, surprise, sense, [and] space”, this article explores the meaning-making and affectmaking practices through the manipulation of white space in poetry. The archive that it draws from is of contemporary Indian poetry, particularly the works of poets Arun Kolatkar (b. 1932), Agha Shahid Ali (b. 1949) and Aditi Rao (b. 1985). Furthering Wagner’s argument that white “space between and around lines create[s]…expectations that are fulfilled or countered by the text” and that organisation of space in poetry “create[s] a sense of drama,” this article studies the varying tactics through which contemporary Indian poets use the device of space to manage meaning and affect in their work.

Parameter Identification of Space Manipulator's Flexible Joint

It is considered to use a manipulator mounted on a satellite in order to perform active debris removal missions. Space manipulator control system needs to take the dynamic model of the satellite-manipulator system into account because of the influence of the manipulator motion on the position and attitude of the satellite. Therefore, precise modelling of the space manipulator dynamics as well as parameter identification are needed in order to improve the credibility of the simulation tools. In this paper we presented the identification of the flexible-joint space manipulator model based on dynamic equations of motion. Experiments were performed in emulated microgravity environment using planar air bearings. The arbitrarily selected joint-space trajectory was performed by the manipulator’s control system. The experiments were repeated multiple times in order to analyze the identification method sensitivity. The identification is based on Simulink SimMechanics model. Thus, the procedure can be used for any space manipulator without the need of obtaining analytical relations for dynamic equations each time. Including joint flexibility and spring viscous damping in the dynamic model allowed to reflect the experimental measurements better than the reference model could. Identified parameters of the flexible joint have values of the same magnitude as corresponding real system parameters.

Adaptive control of BLDC driven robot manipulators in task space

AbstractIn this study, task space tracking control of robot manipulators driven by brushless DC (BLDC) motors is considered. Dynamics of actuators are taken into account and the entire electromechanical system (i.e. kinematic, dynamic, and electrical models) is assumed to include parametric/structured uncertainties. A novel adaptive controller is designed and the stability of the closed loop system is ensured via novel Lyapunov type tools. To demonstrate performance and applicability of the proposed method, a simulation study is conducted using the model of a two degree of freedom, planar robotic manipulator driven by BLDC motors.

Adaptive solution to transfer learning of neural network controllers from earth to space environments

AbstractCompliant manipulation has long been a major constraint for grappling in robotic manipulators. To adopt robotic manipulators in space for the prospect of capturing space junk and transforming them into salvageable assets for re‐use, robust adaptive manipulation would be key. We believe that a bio‐inspired approach could provide human‐like tactility required for robustness and adaptability in robotic manipulation. Given the similarity in form and dynamics between earth‐based and space‐based robotic manipulators, we first explored the transfer learning of neural network controllers as an avenue to address the challenges of limited computation resources onboard the spacecraft (space manipulator). We introduced a pre‐trained and learned feedforward neural network for modelling the control error a priori. While the results were encouraging, there are major limitations of neural networks' capability to ensuring the transfer learning of similar earth‐based dynamics to space‐based dynamics, given that the parameters of contrast are fairly straightforward. We have demonstrated these limitations by presenting a novel approach that is inspired by human motor control. We explored the adaptability through a practical problem of transferring a neuro‐controller from earth to space. With the results not as plausible as expected, an alternative adaptive controller has been learned to demonstrate a viable solution. The controller was trained entirely in simulation via rapid online adaptation of the robot's controller to the object's properties and environmental dynamics using only proprioception history. As a notable step, we have shown that appropriate models can be learned in this manner by training the control policy via reinforcement learning, which provides avenue for transferring the learned model from earth to space environments.

Constrained Fixed-Time Terminal Sliding-Mode Control With Prescribed Performance for Space Manipulator System

Constrained Fixed-Time Terminal Sliding-Mode Control With Prescribed Performance for Space Manipulator System

Free-floating space manipulator impacting a floating object: Modeling and output SDRE controller design

This work investigates the dynamics modeling, control, and impact resolution between a floating object and a free-floating space manipulator (FFSM). The controller design is carried out by using an output- and state-dependent Riccati equation (OSDRE) approach. In a collision between an object and a mechanism, the computation of the generalized velocities and the impact force or impulse, which are interrelated, is a challenging problem. Taking into account the free-floating conditions of the space environment, the conservation of linear and angular momentum equations, combined with the conservation of kinetic energy under the elastic impact assumption, are used to find the unknown variables of the impact problem. The control problem addressed for the FFSM is to regulate its end-effector in a point-to-point motion scenario, this while the space manipulator suffers an unintended impact with a floating object, such as a damaged satellite or space debris. By proposing a safety pause starting with the occurrence of impact and for a short duration thereafter, the proposed OSDRE design succeeds in achieving the end-effector regulation control. Although the FFSM can reach the target point, it is shown that maintaining the end-effector regulation at the target is not feasible due to the momentum imparted to the FFSM as a result of the collision. To this end, we employ a simple thruster control on the space manipulator base to complete the regulation task. The theoretical development and controller design are demonstrated through a simulation case study of a spacecraft equipped with a three-link manipulator colliding with an object.

High-Precision Trajectory Tracking Control for Free-Flying Space Manipulators With Multiple Constraints and System Uncertainties

High-Precision Trajectory Tracking Control for Free-Flying Space Manipulators With Multiple Constraints and System Uncertainties

Robotics should be the mainstream surgical approach in gastrointestinal surgery

The clinical application of robotic gastrointestinal surgery has made significant progress during the past 20 years. Increasing research have demonstrated that the robotic gastrointestinal surgery is safe and feasible, with the advantages in lymph node dissection, precise manipulation in narrow space, intraoperative suturing, and achieves satisfactory clinical outcomes. However, it also face challenges such as high costs, lack of high quality studies, and limited intelligent level. With the advancement of more high-quality evidence-based medical research and the development of new intelligent surgical robots, the robotic gastrointestinal surgery will be further standardized. We believe that the robotic surgery will become the mainstream of surgical treatment for gastrointestinal surgery.

Advanced Technologies and Applications of Robotic Soft Grippers

AbstractThe robotic soft gripper is a significant and expanding area of study. It is primarily a unique gadget that interacts with the external environment in a certain actuating mode by utilizing the properties of flexible materials and biological shape design. Robotic grippers are increasingly needed in the fields of medical operations, auxiliary maintenance, land rescue, underwater grasping, and space manipulation due to the increasing demand for automation. However, conventional rigid gripper is not the ideal option or optimal design for particular activities requiring a high degree of adaptation and interaction. The soft gripper can interact with its surroundings safely and flexibly because it is comprised of flexible materials. Currently, certain technical system has been developed through research on flexible grippers, but it is still in its infancy. This paper reviews the materials and manufacturing technology, actuating technology, and sensing and control technology of flexible mechanical grippers. Finally, several main application areas of soft grippers are discussed from a technical point of view, as well as possible challenges for further development.

Deep MARL-Based Resilient Motion Planning for Decentralized Space Manipulator

Space manipulators play an important role in the on-orbit services and planetary surface operation. In the extreme environment of space, space manipulators are susceptible to a variety of unknown disturbances. How to have a resilient guarantee in failure or disturbance is the core capability of its future development. Compared with traditional motion planning, learning-based motion planning has gradually become a hot spot in current research. However, no matter what kind of research ideas, the single robotic manipulator is studied as an independent agent, making it unable to provide sufficient flexibility under conditions such as external force disturbance, observation noise, and mechanical failure. Therefore, this paper puts forward the idea of “discretization of the traditional single manipulator”. Different discretization forms are given through the analysis of the multi-degree-of-freedom single-manipulator joint relationship, and a single-manipulator representation composed of multiple new subagents is obtained. Simultaneously, to verify the ability of the new multiagent representation to deal with interference, we adopted a centralized multiagent reinforcement learning framework. The influence of the number of agents and communication distances on learning-based planning results is analyzed in detail. In addition, by imposing joint locking failures on the manipulator and introducing observation and action interference, it is verified that the “multiagent robotic manipulator” obtained after discretization has stronger antidisturbance resilient capability than the traditional single manipulator.

Parameters identification and trajectory optimization of free-floating space robots

There is a strong dynamic coupling between the base of free-floating space robot and the space manipulator. In order to reduce the interference of the movement of the space manipulator on the robot's base, the trajectory of the space manipulator needs to be optimized. In this paper, the joint path of space manipulators is optimized by using the pseudo-spectral method to reduce the impact of the arm movement on the base. For space robots, parameters identification is the premise of trajectory planning. A parameters identification method is proposed, which only needs to measure the base's angular speed. Numerical simulation results verify the validity of the proposed method. The attitude angle of floating base returns to the initial state after maneuvers of space manipulators.

A Case of Transanal Endoscopic Excision for Rectal Tumor Using Surgical Instruments With Multi-jointed Structures.

Transanal endoscopic local excision requires fine operation in a very narrow space in the rectum. We report a case in which the use of surgical instruments with a multi-jointed structure allowed safe resection of a lesion with a stable field of view, resulting in preservation of postoperative function. The patient was a 49-year-old man who had a rectal neuroendocrine tumor (NET) (G1) with erosive changes in the lower rectum. Preoperative imaging showed no evidence of surrounding lymph node or distant metastasis; thus, we performed a transanal endoscopic local excision of the tumor. After positioning the patient under general anesthesia and securing the field of view in the intra-rectal cavity, the flexion of the surgical instruments with a multi-jointed structure was used to secure the operating space to not interfere with the camera and the surgeon's right hand. The operating field was developed, and the tumor was incised by stable traction. After the excision, the needle was advanced in the direction of the intestinal axis using the multi-jointed holder, and continuous suturing was performed. The patient has no recurrence without any defecation disorder. The use of multi-jointed surgical instruments in transanal endoscopic excision of rectal tumors can provide a stable operative field and preserve postoperative function. The advanced flexibility of these instruments allows precise manipulation in the narrow rectal space, resulting in successful tumor resection with minimal invasiveness and no postoperative complications. These findings suggest that multi-jointed instruments are valuable for enhancing the safety and efficacy of minimally invasive rectal surgery.

Generating Semantic Adversarial Examples via Feature Manipulation in Latent Space.

The susceptibility of deep neural networks (DNNs) to adversarial intrusions, exemplified by adversarial examples, is well-documented. Conventional attacks implement unstructured, pixel-wise perturbations to mislead classifiers, which often results in a noticeable departure from natural samples and lacks human-perceptible interpretability. In this work, we present an adversarial attack strategy that implements fine-granularity, semantic-meaning-oriented structural perturbations. Our proposed methodology manipulates the semantic attributes of images through the use of disentangled latent codes. We engineer adversarial perturbations by manipulating either a single latent code or a combination thereof. To this end, we propose two unsupervised semantic manipulation strategies: one based on vector-disentangled representation and the other on feature map-disentangled representation, taking into consideration the complexity of the latent codes and the smoothness of the reconstructed images. Our empirical evaluations, conducted extensively on real-world image data, showcase the potency of our attacks, particularly against black-box classifiers. Furthermore, we establish the existence of a universal semantic adversarial example that is agnostic to specific images.

Diffusion Models for Imperceptible and Transferable Adversarial Attack.

Many existing adversarial attacks generate Lp-norm perturbations on image RGB space. Despite some achievements in transferability and attack success rate, the crafted adversarial examples are easily perceived by human eyes. Towards visual imperceptibility, some recent works explore unrestricted attacks without Lp-norm constraints, yet lacking transferability of attacking black-box models. In this work, we propose a novel imperceptible and transferable attack by leveraging both the generative and discriminative power of diffusion models. Specifically, instead of direct manipulation in pixel space, we craft perturbations in the latent space of diffusion models. Combined with well-designed content-preserving structures, we can generate human-insensitive perturbations embedded with semantic clues. For better transferability, we further "deceive" the diffusion model which can be viewed as an implicit recognition surrogate, by distracting its attention away from the target regions. To our knowledge, our proposed method, DiffAttack, is the first that introduces diffusion models into the adversarial attack field. Extensive experiments conducted across diverse model architectures (CNNs, Transformers, and MLPs), datasets (ImageNet, CUB-200, and Standford Cars), and defense mechanisms underscore the superiority of our attack over existing methods such as iterative attacks, GAN-based attacks, and ensemble attacks. Furthermore, we provide a comprehensive discussion on future research avenues in diffusion-based adversarial attacks, aiming to chart a course for this burgeoning field.

Self-Collision Detection and Avoidance for Dual-Arm Concentric Tube Robots

Recent studies on concentric tube robots (CTRs) have shown that they are well-suited for minimally invasive endoscopic surgeries. However, typical surgical procedures require the use of multiple tools simultaneously which has led to the development of dual-arm CTRs that are susceptible to self-collision. In this paper, a closed-loop control system for dual-arm CTRs is proposed to detect and avoid the inter-collision between arms along their entire body. The collision detection module finds the minimum distance between the manipulators in the Cartesian space. To avoid self-collision, the proposed control system using differential Jacobian-based inverse kinematics is developed with three tasks with different priorities; physical constraints, self-collision avoidance, and end-effector tracking. The performance of the proposed control scheme is investigated through implementation for Cartesian control of a dual-arm CTR to reach pre-defined target points in a simulated scenario similar to epilepsy surgery. The self-collision detection module successfully predicted all 359 self-collision cases in the target region. The experimental results demonstrated the efficacy of the controller in handling inter-collision between arms over their entire body by keeping the minimum distance between arms at 1.542 mm.

Model Predictive Control based Coordinated Control for Free-Flying Space Manipulator Systems

Space Manipulator Systems (SMS) used in On-Orbit Servicing (OOS) missions are over-actuated, and safety critical systems that perform complex tasks in space. We propose a coordinated control for a free-flying SMS, which is based on a cascaded output tracking nonlinear model predictive control, to simultaneously control the spacecraft-base and manipulator of the SMS. The output tracks a given end-effector pose trajectory, and by using an artificial reference the controller stays feasible even for an unreachable trajectory. Moreover, the systems over-actuation is optimally resolved, such that the base of the SMS can be utilized to generate an unrestricted workspace for robotic operations. Throughout the entire mission, critical constraints related to system and safety, including collision avoidance, field of view of sensor devices, joint limitations, and actuator saturations, are integrated as hard constraints. Simulations of the most challenging mission phases, such as the approach and detumbling of a target spacecraft, as well as an escape maneuver verify the performance, reliability, and flexibility of our coordinated control concept.

Observer-Based Output Feedback Tracking Control for Flexible Joint Space Manipulator with Output Constraints

Observer-Based Output Feedback Tracking Control for Flexible Joint Space Manipulator with Output Constraints

Controllable Degree Analysis of Space Manipulators with Free-Swing Joint Failure

Controllable Degree Analysis of Space Manipulators with Free-Swing Joint Failure

Design and Implementation of Space Manipulator Operating Subsystem

Design and Implementation of Space Manipulator Operating Subsystem

Манипуляция массовым сознанием: принципы и практика

Today, political manipulation of the masses, mass political consciousness and mass political behavior is not only a common phenomenon, but has also become everyday political practice. Studying this is an urgent theoretical and practical task. This study is aimed at systematizing various theories, methods, techniques and practices of influencing our psyche, using the features of our anthropic development, which we understand as means of manipulation or as objective control of the subject’s consciousness. The results of the study are presented in a thesis-presentation format to counteract external control and reflection. Although the presented results do not claim to be absolutely complete, they contain a sufficient set of common techniques used in marketing, propaganda, information, cognitive and mental wars. The first part of the study is devoted to cognition and techniques for manipulating cognition. The second part, building on the first, contains a description of psi effects used by manipulative attackers, which are associated with our cognitive characteristics. The third part is devoted to methods of manipulation in the media space. The fourth section of the study examines meanings, semantic or mental wars and, based on this epistemology, manipulation of socio-political processes or political wars.