Space Manipulator Research Articles

Obstacle Avoidance Path Planning of Space Robot Based on Improved Particle Swarm Optimization

In order to meet security requirements of space on orbit service, an obstacle avoidance trajectory planning method using improved particle swarm optimization had been presented in this paper. On the basis of the actual overall structure of 7 degrees of freedom redundant space manipulator and the characteristics of obstacles, the envelope method was used to model the arm and obstacles, respectively. The limit conditions to avoid the collision between them were analyzed. Then, the fitness function under the symmetrical conditions of avoiding the collision and searching for the shortest trajectory was constructed. In addition, the obstacle avoidance trajectory planning was solved based on improved particle swarm optimization (IPSO). Finally, simulation experiments were carried out to prove its effectiveness and rationality, where there were symmetrical advantages in two aspects. It can be concluded that the presented method based on IPSO has strong robustness.

Path Planning and Optimization of Humanoid Manipulator in Cartesian Space

Path Planning and Optimization of Humanoid Manipulator in Cartesian Space

Discovering ancient cave art using 3D photogrammetry: pre-contact Native American mud glyphs from 19thUnnamed Cave, Alabama

Since 1979, when the first cave art was documented in North America, dozens of other examples have come to light. Among these, 19thUnnamed Cave in Alabama contains hundreds of pre-contact Native American mud glyph drawings. In 2017, 3D modelling of the glyphs was initiated, ultimately enabling digital manipulation of the chamber space and revealing images that could not be perceived prior to modelling. Most surprisingly, the cave's ceiling features very large anthropomorphic glyphs that are not apparentin situdue to the tight confines of the cave. We argue that photogrammetry offers untapped potential for not simply the documentation but also the discovery of a variety of archaeological phenomena.

Direct Trajectory Optimization of Free-Floating Space Manipulator for Reducing Spacecraft Variation

This letter investigates the direct trajectory optimization of the free-floating space manipulator (FFSM). The main purpose is to plan the joint space trajectories to reduce the spacecraft motion due to the joint rotation during the FFSM performing tasks. To improve the calculation efficiency, the adaptive Radau pseudospectral method (A-RPM) is applied to discretize the system dynamics and transform the formulated optimal problem into a nonlinear programming problem (NLP). By adaptively subdividing the current segment and assigning collocation points according to the solution error, high-degree interpolation polynomials are avoided. To verify the effectiveness of the proposed method, a ground micro-gravity platform of the FFSM system is designed by using the air-bearing technique, on which experiments are carried out. The results show that the variation of the base spacecraft is dramatically reduced if the joints rotate along the optimized trajectories.

Trajectory Generation for Flexible-Joint Space Manipulators

Space manipulator arms often exhibit significant joint flexibility and limited motor torque. Future space missions, including satellite servicing and large structure assembly, may involve the manipulation of massive objects, which will accentuate these limitations. Currently, astronauts use visual feedback on-orbit to mitigate oscillations and trajectory following issues. Large time delays between orbit and Earth make ground teleoperation difficult in these conditions, so more autonomous operations must be considered to remove the astronaut resource requirement and expand robotic capabilities in space. Trajectory planning for autonomous systems must therefore be considered to prevent poor trajectory tracking performance. We provide a model-based trajectory generation methodology that incorporates constraints on joint speed, motor torque, and base actuation for flexible-joint space manipulators while minimizing total trajectory time. Full spatial computer simulation results, as well as physical experiment results with a single-joint robot on an air bearing table, show the efficacy of our methodology.

Education of students in the conditions of digitalization of inclusive higher education

The article reflects the problem of using virtual networks as a means of education in the educational process of the university, presents the results of experimental work aimed at determining the propensity to socially acceptable forms of addictions and their prevention in future psychologists and teachers-psychologists by means of psychotechnologies implemented within the framework of educational work in a remote format, which are aimed at forming the intrapersonal potential of ensuring a safe existence, psychological security in interpersonal interaction in the conditions of electronic communication and neutralization of threats and manipulation in the information space.

Particle Manipulation in 2D Space Using a Capacitive Micromachined Ultrasonic Transducer.

Ultrasonic particle manipulation is a noncontact method for controlling microscale objects, such as cells or microparticles, using an acoustic field. In this study, a 2D array of capacitive micromachined ultrasonic transducers (CMUTs), placed horizontally in immersion, generated ultrasonic waves in the vertical direction, and the oil’s surface increased due to the radiation force of the ultrasonic waves. In addition, the radiation force directly exerted a force on a floating particle. By measuring the movement of the reflected laser light by the moving oil surface, the height of the oil’s surface deformed by the acoustic radiation force (ARF) was measured. The ARF made a floating particle, as well as the oil’s surface, move. The particle moved radially away from the surface position above the transducer, and its velocity was determined by its position on the fluid’s surface. When a single channel was operated, it moved 0.4 mm at an average speed of 90 μm/s, and when two adjacent channels were operated, it moved 1.2 mm at a speed of 272 μm/s. The particles moved in any direction on the surface of the oil by controlling the actuation channel using an electrical switch.

Optimal detumbling strategy for a non-cooperative target with unknown inertial parameters using a space manipulator

Capturing tumbling target is considered as one of the greatest challenges in on-orbit service missions due to tumbling motion and parameter uncertainty of the space non-cooperative target. The tumbling motion of the target should be attenuated as quickly as possible before grasping to avoid the unexpected collisions and possible damages to the space manipulator or the target, which means the shortest-time detumbling trajectory is necessary. In many studies about the optimal detumbling trajectory planning the inertial parameters of the target have been assumed to be accurately known, which is usually difficult for a non-cooperative target so that parameter identification is needed before planning a optimal detumbling trajectory. In this paper, a novel strategy for parameter identification and detumbling of a tumbling target by a space manipulator is proposed. The strategy includes two phases. First, unknown inertial parameters of the target are identified in finite-time by a new estimation method with the assumption of interval excitation (IE), which relaxes the strict persistent excitation (PE) condition required in most prior studies. Second, the shortest-time detumbling trajectory of the tumbling target is generated by formulating a time-optimal control problem (OCP) in which the target attitude bounds and the limitations of the contact force as well as the relative velocity between the space manipulator and the target are represented as extended dynamical sub-systems and saturation functions. Then, the Calculus of Variations method is used to solve the OCP to obtain a high accuracy solution. During two phases, the contact force between the space manipulator and the target is utilized to generate external moment for identifying the inertia parameters of the target and detumbling the target. Meanwhile, a unified hybrid impedance control framework is applied to the space robot to track the desired contact force and motion trajectory. The whole strategy is verified by a space manipulator capturing a tumbling target, and numerical simulations demonstrate the effectiveness of the proposed methods.

Deep Generative Models for Materials Discovery and Machine Learning-Accelerated Innovation

Machine learning and artificial intelligence (AI/ML) methods are beginning to have significant impact in chemistry and condensed matter physics. For example, deep learning methods have demonstrated new capabilities for high-throughput virtual screening, and global optimization approaches for inverse design of materials. Recently, a relatively new branch of AI/ML, deep generative models (GMs), provide additional promise as they encode material structure and/or properties into a latent space, and through exploration and manipulation of the latent space can generate new materials. These approaches learn representations of a material structure and its corresponding chemistry or physics to accelerate materials discovery, which differs from traditional AI/ML methods that use statistical and combinatorial screening of existing materialsviadistinct structure-property relationships. However, application of GMs to inorganic materials has been notably harder than organic molecules because inorganic structure is often more complex to encode. In this work we review recent innovations that have enabled GMs to accelerate inorganic materials discovery. We focus on different representations of material structure, their impact on inverse design strategies using variational autoencoders or generative adversarial networks, and highlight the potential of these approaches for discovering materials with targeted properties needed for technological innovation.

Analysis of translation gains in virtual reality: the limits of space manipulation

Analysis of translation gains in virtual reality: the limits of space manipulation

Constrained Motion Planning of 7-DOF Space Manipulator via Deep Reinforcement Learning Combined with Artificial Potential Field

During the on-orbit operation task of the space manipulator, some specific scenarios require strict constraints on both the position and orientation of the end-effector, such as refueling and auxiliary docking. To this end, a novel motion planning approach for a space manipulator is proposed in this paper. Firstly, a kinematic model of the 7-DOF free-floating space manipulator is established by introducing the generalized Jacobian matrix. On this basis, a planning approach is proposed to realize the motion planning of the 7-DOF free-floating space manipulator. Considering that the on-orbit environment is dynamical, the robustness of the motion planning approach is required, thus the deep reinforcement learning algorithm is introduced to design the motion planning approach. Meanwhile, the deep reinforcement learning algorithm is combined with artificial potential field to improve the convergence. Besides, the self-collision avoidance constraint is considered during planning to ensure the operational security. Finally, comparative simulations are conducted to demonstrate the performance of the proposed planning method.

Control of a Robotic Arm With an Optimized Common Template-Based CCA Method for SSVEP-Based BCI.

Recently, the robotic arm control system based on a brain-computer interface (BCI) has been employed to help the disabilities to improve their interaction abilities without body movement. However, it's the main challenge to implement the desired task by a robotic arm in a three-dimensional (3D) space because of the instability of electroencephalogram (EEG) signals and the interference by the spontaneous EEG activities. Moreover, the free motion control of a manipulator in 3D space is a complicated operation that requires more output commands and higher accuracy for brain activity recognition. Based on the above, a steady-state visual evoked potential (SSVEP)-based synchronous BCI system with six stimulus targets was designed to realize the motion control function of the seven degrees of freedom (7-DOF) robotic arm. Meanwhile, a novel template-based method, which builds the optimized common templates (OCTs) from various subjects and learns spatial filters from the common templates and the multichannel EEG signal, was applied to enhance the SSVEP recognition accuracy, called OCT-based canonical correlation analysis (OCT-CCA). The comparison results of offline experimental based on a public benchmark dataset indicated that the proposed OCT-CCA method achieved significant improvement of detection accuracy in contrast to CCA and individual template-based CCA (IT-CCA), especially using a short data length. In the end, online experiments with five healthy subjects were implemented for achieving the manipulator real-time control system. The results showed that all five subjects can accomplish the tasks of controlling the manipulator to reach the designated position in the 3D space independently.

Time delay estimation-based reactionless augmented adaptive sliding mode control of a space manipulator’s pregrasping a target

AbstractReaction null space (RNS) planning and control of a planar three-link space manipulator’s pregrasping a spinning target are studied. First, the Lagrange dynamic model of the manipulator was established. Second, the RNS motion planning algorithm was derived, and the vector norm constraint algorithm of RNS planning was addressed to ensure certain joint angular acceleration constraints were satisfied. Furthermore, an augmented adaptive sliding mode controller based on time delay estimation (TDE) was proposed. This controller estimated the unknowns of the system by TDE technology, in which accurate and complete dynamics were not required, and an adaptive TDE was introduced to decrease the estimation errors and avoid serious chattering. Finally, numerical simulations were carried out to verify the effectiveness of the proposed RNS planning and control algorithm.

The Discourse of Propaganda: Case Studies from the Persian Gulf War and the War on Terror

The Discourse of Propaganda: Case Studies from the Persian Gulf War and the War on Terror

Strong anion exchange for improved NiCo2S4 oxygen reduction reaction via interlayer spacing manipulation

Transition metal sulfides as high-performance, cost-effective, and stable electrocatalysts for oxygen reduction reaction (ORR) have attracted much attention. The replacement of sulfur atom by oxygen atom in metal sulfides was considered to be the fundamental reason for its decreased activity. Adequate anion exchange can greatly reduce the generation of oxygen species in transition metal sulfide, which further enhances the intrinsic electrical conductivity and stability of transition metal sulfides. Herein, a novel and simple approach to larger interlayer spacing was provided by introducing interlayer water in layered hydroxides precursor. The NCS-O 1 with treated layered hydroxides precursor exhibits few oxygen impurities and excellent activity for the ORR in alkaline electrolyte, presenting the close limiting diffusion current density and lower Tafel slope (reaches 56 mV dec −1 , vs. Pt/C 70) in comparison to 20% commercial Pt/C. Hence, our results provide an interesting design path for such catalysts. • A novel approach to synthesize NiCo 2 S 4 with few oxygen impurities. • The larger interlayer spacing in Ni–Co hydroxide favors the anion exchange. • The oxygen incorporation in NiCo 2 S 4 causes lower d-band center of metal sites. • The decreased oxygen impurities in NiCo 2 S 4 are conducive to oxygen reduction.

The obstacle vector field (OVF) method for collision-free trajectory planning of free-floating space manipulator

The obstacle vector field (OVF) method for collision-free trajectory planning of free-floating space manipulator

Disturbance observer-based robust fixed-time integrated trajectory tracking control for space manipulator

AbstractThis article investigates the fixed-time trajectory tracking control of a free-flying rigid space manipulator perturbed by model uncertainties and external disturbances. A novel robust fixed-time integrated controller is developed by integrating a nominal fixed-time proportional–differential-like controller with a fixed-time disturbance observer. It is strictly proved that the proposed controller can ensure the position and velocity tracking errors regulate to zero in fixed time even subject to lumped disturbance. Benefiting from the feedforward compensation, the proposed controller has the strong robustness and excellent disturbance attenuation capability. The effectiveness and advantages of the proposed control approach are validated through simulations and comparisons.

TARA: Training and Representation Alteration for AI Fairness and Domain Generalization.

We propose a novel method for enforcing AI fairness with respect to protected or sensitive factors. This method uses a dual strategy performing training and representation alteration (TARA) for the mitigation of prominent causes of AI bias. It includes the use of representation learning alteration via adversarial independence to suppress the bias-inducing dependence of the data representation from protected factors and training set alteration via intelligent augmentation to address bias-causing data imbalance by using generative models that allow the fine control of sensitive factors related to underrepresented populations via domain adaptation and latent space manipulation. When testing our methods on image analytics, experiments demonstrate that TARA significantly or fully debiases baseline models while outperforming competing debiasing methods that have the same amount of information-for example, with (% overall accuracy, % accuracy gap) = (78.8, 0.5) versus the baseline method's score of (71.8, 10.5) for Eye-PACS, and (73.7, 11.8) versus (69.1, 21.7) for CelebA. Furthermore, recognizing certain limitations in current metrics used for assessing debiasing performance, we propose novel conjunctive debiasing metrics. Our experiments also demonstrate the ability of these novel metrics in assessing the Pareto efficiency of the proposed methods.

TDE-Based Adaptive Integral Sliding Mode Control of Space Manipulator for Space-Debris Active Removal

The safe and dependable removal of large-scale space debris has been a long-standing challenge that is critical to the safety of spacecraft and astronauts. In the process of capturing and deorbiting space debris, the space manipulator must achieve extremely high control and precision. However, strong couplings, model uncertainties, and various inevitable unknown disturbances cause many difficulties in coordinated control of the space manipulator. To solve this challenge, this study examines the stabilization control of a space manipulator after capturing non-cooperative large-scale space debris and presents an adaptive integral sliding mode control (AISMC) scheme with time-delay estimation (TDE). The coupling term and lumped uncertainty are estimated by TDE technology, which eliminates the requirement of prior knowledge. Adaptive sliding mode control (ASMC) is used as desired injecting dynamics to compensate TDE errors, and a PID-type integral sliding mode surface is designed to reduce steady-state errors. The Lyapunov criterion is used to prove the global stability of the controller. Simulation results show that the controller has high tracking accuracy and strong robustness.

‘Can You Hear My Cry?’ Representing War and Trauma in Picturebooks for Peace from China, South Korea, and Japan

This article discusses the Picturebooks for Peace series, a collaboration between China, South Korea, and Japan focusing primarily upon World War II. In examining this series, we ask what these works are testifying to, how they represent trauma, and how picturebooks from countries with distinct political and cultural outlooks have been conceived and received in the different milieus. Our major contention is that it is through the manipulation of time and space that the creators of these works seek to persuade readers of the validity of their message. We look first at the picturebooks from China and South Korea, which share an ideological position inasmuch as they use the trauma caused by the Japanese invasion and its aftermath (including the Korean War) to criticise war's inhumanity. The second part of the article deals with the four Japanese picturebooks, which reflect on the reasons for or essence of war. The article then discusses the narrative and aesthetic devices these books employ to represent war.