Lunar rock investigation and tri-aspect characterization of lunar farside regolith by a digital twin.

Yutu-2 rover conducted an exciting expedition on the 41st lunar day to investigate a fin-shaped rock at Longji site (45.44°S, 177.56°E) by extending its locomotion margin on perilous peaks. The varied locomotion encountered, especially multi-form wheel slippage, during the journey to the target rock, established unique conditions for a fin-grained lunar regolith analysis regarding bearing, shear and lateral properties based on terramechanics. Here, we show a tri-aspect characterization of lunar regolith and infer the rock's origin using a digital twin. We estimate internal friction angle within 21.5°-42.0° and associated cohesion of 520-3154 Pa in the Chang'E-4 operational site. These findings suggest shear characteristics similar to Apollo 12 mission samples but notably higher cohesion compared to regolith investigated on most nearside lunar missions. We estimate external friction angle in lateral properties to be within 8.3°-16.5°, which fills the gaps of the lateral property estimation of the lunar farside regolith and serves as a foundational parameter for subsequent engineering verifications. Our in-situ spectral investigations of the target rock unveil its composition of iron/magnesium-rich low-calcium pyroxene, linking it to the Zhinyu crater (45.34°S, 176.15°E) ejecta. Our results indicate that the combination of in-situ measurements with robotics technology in planetary exploration reveal the possibility of additional source regions contributing to the local materials at the Chang'E-4 site, implying a more complicated geological history in the vicinity.

Vibration-Based Recognition of Wheel-Terrain Interaction for Terramechanics Model Selection and Terrain Parameter Identification for Lugged-Wheel Planetary Rovers.

Identifying terrain parameters is important for high-fidelity simulation and high-performance control of planetary rovers. The wheel-terrain interaction classes (WTICs) are usually different for rovers traversing various types of terrain. Every terramechanics model corresponds to its wheel-terrain interaction class (WTIC). Therefore, for terrain parameter identification of the terramechanics model when rovers traverse various terrains, terramechanics model switching corresponding to the WTIC needs to be solved. This paper proposes a speed-independent vibration-based method for WTIC recognition to switch the terramechanics model and then identify its terrain parameters. In order to switch terramechanics models, wheel-terrain interactions are divided into three classes. Three vibration models of wheels under three WTICs have been built and analyzed. Vibration features in the models are extracted and non-dimensionalized to be independent of wheel speed. A vibration-feature-based recognition method of the WTIC is proposed. Then, the terrain parameters of the terramechanics model corresponding to the recognized WTIC are identified. Experiment results obtained using a Planetary Rover Prototype show that the identification method of terrain parameters is effective for rovers traversing various terrains. The relative errors of estimated wheel-terrain interaction force with identified terrain parameters are less than 16%, 12%, and 9% for rovers traversing hard, gravel, and sandy terrain, respectively.

NN-Based Reinforcement Learning Optimal Control for Inequality-Constrained Nonlinear Discrete-Time Systems With Disturbances.

Based on actor-critic neural networks (NNs), an optimal controller is proposed for solving the constrained control problem of an affine nonlinear discrete-time system with disturbances. The actor NNs provide the control signals and the critic NNs work as the performance indicators of the controller. By converting the original state constraints into new input constraints and state constraints, the penalty functions are introduced into the cost function, and then the constrained optimal control problem is transformed into an unconstrained one. Further, the relationship between the optimal control input and worst-case disturbance is obtained using the Game theory. With Lyapunov stability theory, the control signals are ensured to be uniformly ultimately bounded (UUB). Finally, the effectiveness of the control algorithms is tested through a numeral simulation using a third-order dynamic system.

Design and Simulation of On-Orbit Assembly System Based on Insect-Inspired Transportation.

In response to the requirements of large-scale space in-orbit assembly and the special environment of low gravity in space, this paper proposes a small robot structure with the integration of assembly, connection, and vibration reduction functionalities. Each robot consists of a body and three composite mechanical arms-legs, which can dock and transfer assembly units with the transport spacecraft unit, and also crawl along the edge truss of the assembly unit to a designated location to complete in-orbit assembly while ensuring precision. A theoretical model of robot motion was established for simulation studies, and in the research process, the vibration of the assembly unit was studied, and preliminary adjustments were made to address the vibration issue. The results show that this structure is feasible for in-orbit assembly schemes and has good adjustment ability for flexible vibration.

Learning physical characteristics like animals for legged robots.

Physical characteristics of terrains, such as softness and friction, provide essential information for legged robots to avoid non-geometric obstacles, like mires and slippery stones, in the wild. The perception of such characteristics often relies on tactile perception and vision prediction. Although tactile perception is more accurate, it is limited to close-range use; by contrast, establishing a supervised or self-supervised contactless prediction system using computer vision requires adequate labeled data and lacks the ability to adapt to the dynamic environment. In this paper, we simulate the behavior of animals and propose an unsupervised learning framework for legged robots to learn the physical characteristics of terrains, which is the first report to manage it online, incrementally and with the ability to solve cognitive conflicts. The proposed scheme allows robots to interact with the environment and adjust their cognition in real time, therefore endowing robots with the adaptation ability. Indoor and outdoor experiments on a hexapod robot are carried out to show that the robot can extract tactile and visual features of terrains to create cognitive networks independently; an associative layer between visual and tactile features is created during the robot's exploration; with the layer, the robot can autonomously generate a physical segmentation model of terrains and solve cognitive conflicts in an ever-changing environment, facilitating its safe navigation.

Highly Accurate Visual Method of Mars Terrain Classification for Rovers Based on Novel Image Features.

It is important for Mars exploration rovers to achieve autonomous and safe mobility over rough terrain. Terrain classification can help rovers to select a safe terrain to traverse and avoid sinking and/or damaging the vehicle. Mars terrains are often classified using visual methods. However, the accuracy of terrain classification has been less than 90% in read operations. A high-accuracy vision-based method for Mars terrain classification is presented in this paper. By analyzing Mars terrain characteristics, novel image features, including multiscale gray gradient-grade features, multiscale edges strength-grade features, multiscale frequency-domain mean amplitude features, multiscale spectrum symmetry features, and multiscale spectrum amplitude-moment features, are proposed that are specifically targeted for terrain classification. Three classifiers, K-nearest neighbor (KNN), support vector machine (SVM), and random forests (RF), are adopted to classify the terrain using the proposed features. The Mars image dataset MSLNet that was collected by the Mars Science Laboratory (MSL, Curiosity) rover is used to conduct terrain classification experiments. The resolution of Mars images in the dataset is 256 × 256. Experimental results indicate that the RF classifies Mars terrain at the highest level of accuracy of 94.66%.

Development of a generator for percussive ultrasonic drills used in asteroid exploration based on impedance characteristics analysis.

Percussive ultrasonic drills participate in asteroid exploration missions. Since space environments are complex and working loads vary dramatically, it is necessary to design a drive that better matches the percussive ultrasonic drill to make it achieve high-speed drilling with low power consumption. Impedance characteristics under different load conditions and the load varying in one drilling cycle are investigated based on analyzing the working principle of the percussive ultrasonic drill. An ultrasonic drill driver with automatic scanning resonant frequency and digital phase-locked loop frequency tracking control is designed according to the load characteristics. Series capacitance impedance matching ultrasonic drills is experimentally studied. Vibration amplitude and impedance characteristics of the ultrasonic drill driven by the designed driver are measured to evaluate the frequency tracking ability and the impedance matching. Finally, ultrasonic drilling experiments are conducted in room, low, and high temperature environments to investigate the driving performance. Under room temperature and 5 N drilling pressure, the speed of ultrasonic drilling into soft sandstone is 52 mm/min, and the power consumption is less than 70 W. The experimental results indicate that the designed driver can drive the percussive ultrasonic drill to achieve stable and high-speed drilling with low power consumption and low drilling pressure.

Biomimetic folding of triangular deployable membranes.

Deployable membranes are being increasingly applied in numerous space projects owing to their light weight, small stowage volume and capacity for use at large scales. The geometric design of biomimetic folding is studied to design crease patterns for triangular deployable membranes applied in space. Various crease designs for triangular membranes based on leaf-in, leaf-out and orthogonal patterns are put forward, especially patterns composed of triangular and hexagonal units. In order to analyse the membrane folding method based on biomimetic folding, a set of evaluation indices, including linear dimension ratio, deployment ratio, crease length and junction number, are established. The indices for various membrane folding patterns are calculated according to the crease distributions and geometric relations. Furthermore, a parametric study of crease parameters is performed to determine how the parameters affect folding behaviour and deployment efficiency. These indices can provide an indication to help with the selection of crease patterns and folding parameters for triangular deployable membranes according to the required performance and space mission requirements.

Adaptive Fuzzy Finite-Time Tracking Control for Nonstrict Full States Constrained Nonlinear System With Coupled Dead-Zone Input.

This article proposes an adaptive finite-time tracking control based on fuzzy-logic systems (FLSs) for an uncertain nonstrict nonlinear multi-input-multi-output (MIMO) full-state-constrained system with the coupled uncertain dead-zone input. By using three kinds of FLSs: the uncertain system, the uncertain dead zone, and the uncertain input transfer inverse matrix are approximated using the system function FLS, dead-zone FLS, and input transfer inverse matrix FLS, respectively. After defining the barrier Lyapunov function, the fuzzy-based adaptive tracking controllers are designed, and the fuzzy weights are updated through the proposed adaptive laws. Then, based on the extended finite-time convergence theorem, with the design parameters chosen properly, the target uncertain nonlinear system is guaranteed to be semiglobal practical finite-time stable (SGPFS); and the full-state constraints are not violated while avoiding the effects of the dead zones. Furthermore, a simulation is presented to verify the validity of the proposed algorithm.

Adaptive Neural Network-Based Finite-Time Online Optimal Tracking Control of the Nonlinear System With Dead Zone.

Considering the uncertain nonstrict nonlinear system with dead-zone input, an adaptive neural network (NN)-based finite-time online optimal tracking control algorithm is proposed. By using the tracking errors and the Lipschitz linearized desired tracking function as the new state vector, an extended system is present. Then, a novel Hamilton-Jacobi-Bellman (HJB) function is defined to associate with the nonquadratic performance function. Further, the upper limit of integration is selected as the finite-time convergence time, in which the dead-zone input is considered. In addition, the Bellman error function can be obtained from the Hamiltonian function. Then, the adaptations of the critic and action NN are updated by using the gradient descent method on the Bellman error function. The semiglobal practical finite-time stability (SGPFS) is guaranteed, and the tracking errors convergence to a compact set by zero in a finite time.

Atomistic Simulation Study of Nanoparticle Effect on Nano-Cutting Mechanisms of Single-Crystalline Materials.

Nanoparticle (NP), as a kind of hard-to-machine component in nanofabrication processes, dramatically affects the machined surface quality in nano-cutting. However, the surface/subsurface generation and the plastic deformation mechanisms of the workpiece still remain elusive. Here, the nano-cutting of a single-crystalline copper workpiece with a single spherical embedded nanoparticle is explored using molecular dynamics (MD) simulations. Four kinds of surface/subsurface cases of nanoparticle configuration are revealed, including being removed from the workpiece surface, moving as a part of the cutting tool, being pressed into the workpiece surface, and not interacting with the cutting tool, corresponding to four kinds of relative depth ranges between the center of the nanoparticle and the cutting tool. Significantly different plastic deformation mechanisms and machined surface qualities of the machined workpiece are also observed, suggesting that the machined surface quality could be improved by adjusting the cutting depth, which results in a change of the relative depth. In addition, the nanoparticle also significantly affects the processing forces in nano-cutting, especially when the cutting tool strongly interacts with the nanoparticle edge.

ADP-Based Online Tracking Control of Partially Uncertain Time-Delayed Nonlinear System and Application to Wheeled Mobile Robots.

In this paper, an adaptive dynamic programming-based online adaptive tracking control algorithm is proposed to solve the tracking problem of the partial uncertain time-delayed nonlinear affine system with uncertain resistance. Using the discrete-time Hamilton-Jacobi-Bellman function, the input time-delay separation lemma, and the Lyapunov-Krasovskii functionals, the partial state and input time delay can be determined. With the approximation of the action and critic, and resistance neural networks, a near-optimal controller and appropriate adaptive laws are defined to guarantee the uniform ultimate boundedness of all signals in the target system, and the tracking error convergence to a small compact set to zero. A numerical simulation of the wheeled mobile robotic system is presented to verify the validity of the proposed method.

Measurement Model and Precision Analysis of Accelerometers for Maglev Vibration Isolation Platforms.

High precision measurement of acceleration levels is required to allow active control for vibration isolation platforms. It is necessary to propose an accelerometer configuration measurement model that yields such a high measuring precision. In this paper, an accelerometer configuration to improve measurement accuracy is proposed. The corresponding calculation formulas of the angular acceleration were derived through theoretical analysis. A method is presented to minimize angular acceleration noise based on analysis of the root mean square noise of the angular acceleration. Moreover, the influence of installation position errors and accelerometer orientation errors on the calculation precision of the angular acceleration is studied. Comparisons of the output differences between the proposed configuration and the previous planar triangle configuration under the same installation errors are conducted by simulation. The simulation results show that installation errors have a relatively small impact on the calculation accuracy of the proposed configuration. To further verify the high calculation precision of the proposed configuration, experiments are carried out for both the proposed configuration and the planar triangle configuration. On the basis of the results of simulations and experiments, it can be concluded that the proposed configuration has higher angular acceleration calculation precision and can be applied to different platforms.

Path-following control of wheeled planetary exploration robots moving on deformable rough terrain.

The control of planetary rovers, which are high performance mobile robots that move on deformable rough terrain, is a challenging problem. Taking lateral skid into account, this paper presents a rough terrain model and nonholonomic kinematics model for planetary rovers. An approach is proposed in which the reference path is generated according to the planned path by combining look-ahead distance and path updating distance on the basis of the carrot following method. A path-following strategy for wheeled planetary exploration robots incorporating slip compensation is designed. Simulation results of a four-wheeled robot on deformable rough terrain verify that it can be controlled to follow a planned path with good precision, despite the fact that the wheels will obviously skid and slip.