Multiple Degrees Of Freedom Research Articles

Non-holonomic constraints-based adaptive trajectory tracking controller for a multi-joint snake robot

The multi-joint snake robot is poised to become a crucial asset for investigation, surveillance, and attack in national defense and military applications. This paper addresses the trajectory tracking challenge of a multi-joint snake robot characterized by high redundancy and multiple degrees of freedom in the plane. We propose an adaptive trajectory tracking controller that accounts for non-holonomic constraints. This controller estimates unknown environmental parameters, effectively mitigating the negative impacts of uncertain and time-varying conditions during robot movement, thereby ensuring stability. A suitable Lyapunov function is identified to confirm the controller’s stability. The trajectory tracking performance of the robot is thoroughly analyzed through simulations and experiments, demonstrating the effectiveness of the proposed adaptive controller.

Double-spiral as a bio-inspired functional element in engineering design

Spiral, one of the most well-known functional patterns in nature that can be observed in structures such as the proboscis of lepidoptera and snail shells or as vortices forming in flowing fluids, has long served as a source of inspiration for humans in the creation of numerous spiral-based designs. Double-spiral is a design derived from spirals, which has been previously presented and utilized as a compliant joint. Advantageous properties of double-spirals, such as easily adjustable design, multiple degrees of freedom, reversible extensibility, and tunable deformability make them promising candidates for the development of mechanically intelligent structures that exhibit unique behavior and reach desired functions, such as soft grippers, continuum manipulators, energy-dissipative structures, and foldable metamaterials. In this article, we first develop the Double-Spiral Design software to facilitate the design and modeling of double-spirals. We then design and manufacture five different spiral-based structures using three-dimensional (3D) printing, including (1) a freeform passive gripper, (2) a highly extensible enveloping gripper, (3) a mechanical interlocking structure, (4) an adaptive energy-dissipative structure, and (5) a compliant planar joint. Through practical experimentation, we test the functionality of the developed structures and showcase the potential of double-spirals for being used in various technical applications. This study represents a significant step towards a better understanding of double-spirals and demonstrates their broad but unexplored potential in engineering design.

Scattering between orthogonally wobbling kinks

The resonant energy transfer mechanism, responsible for the presence of fractal patterns in the velocity diagrams of kink-antikink scattering, is analyzed for a family of two-component scalar field theory models, in which the kink solutions have two shape modes (one longitudinal and one orthogonal to the kink orbit), in addition to the zero mode, and in which energy redistribution can occur among these three discrete modes. We investigate the scattering between wobbling kinks whose orthogonal shape mode is initially excited, examining how the final velocities, amplitudes, and frequencies depend on the initial excitation amplitude. The differences that this model presents with respect to the ϕ4 model and its novel properties are highlighted. This analysis sheds light on the intricate dynamics that arise from the interplay between multiple degrees of freedom in kink scattering processes, offering insights distinct from those observed in simpler models.

Bioinspired Microhinged Actuators for Active Mechanism‐Based Metamaterials

AbstractMechanism‐based metamaterials, comprising rigid elements interconnected by flexible hinges, possess the potential to develop intelligent micromachines with programmable motility and morphology. However, the absence of efficient microactuators has constrained the ability to achieve multimodal locomotion and active shape‐morphing behaviors at the micro and nanoscale. In this study, inspiration from the flight mechanisms of tiny insects is drawn to develop a biomimetic microhinged actuator by integrating compliant mechanisms with soft hydrogel muscle. A Pseudo‐Rigid‐Body mechanical model is introduced to analyze structural deformation, demonstrating that this hydrogel‐based microactuator can undergo significant folding while maintaining high structural stiffness. Furthermore, multiple microhinged actuators are combined to facilitate folding in multiple degrees of freedom and arbitrary directions. Fabricated by a multi‐step four‐dimensional (4D) direct laser writing technique, the microhinged actuators are integrated into 2D and 3D metamaterials enabling programable shape morphing. Additionally, micro‐kirigami with photonic structures is demonstrated to show the pattern transforming actuated by the microhinges. This bioinspired design approach opens new avenues for the development of active mechanism‐based metamaterials capable of intricate shape‐morphing behaviors.

Development of a Robot-Assisted Fused Deposition Modeling Process for Enhanced Additive Manufacturing

<div>This work aims to define a novel integration of 6 DOF robots with an extrusion-based 3D printing framework that strengthens the possibility of implementing control and simulation of the system in multiple degrees of freedom. Polylactic acid (PLA) is used as an extrusion material for testing, which is a thermoplastic that is biodegradable and is derived from natural lactic acid found in corn, maize, and the like. To execute the proposed framework a virtual working station for the robot was created in RoboDK. RoboDK interprets G-code from the slicing (Slic3r) software. Further analysis and experiments were performed by FANUC 2000ia 165F Industrial Robot. Different tests were performed to check the dimensional accuracy of the parts (rectangle and cylindrical). When the robot operated at 20% of its maximum speed, a bulginess was observed in the cylindrical part, causing the radius to increase from 1 cm to 1.27 cm and resulting in a thickness variation of 0.27 cm at the bulginess location. However, after optimizing the speed at 35% of its maximum speed, 100% dimensional accuracy was achieved. The integration resulted in collision-free robot and extrusion movement, flexibility, capability of making large parts, and enhanced dimensional accuracy.</div>

Focal volume optics for composite structuring in transparent solids

Abstract Achieving high-level integration of composite micro-nano structures with different structural characteristics through a minimalist and universal process has long been the goal pursued by advanced manufacturing research but is rarely explored due to the absence of instructive mechanisms. Here, we revealed a controllable ultrafast laser-induced focal volume light field and experimentally succeeded in highly efficient one-step composite structuring in multiple transparent solids. A pair of spatially coupled twin periodic structures reflecting light distribution in the focal volume are simultaneously created and independently tuned by engineering ultrafast laser-matter interaction. We demonstrated that the generated composite micro-nano structures are applicable to multi-dimensional information integration, nonlinear diffractive elements, and multi-functional optical modulation. This work presents the experimental verification of highly universal all-optical fabrication of composite micro-nano structures with independent controllability in multiple degrees of freedom, expands the current cognition of ultrafast laser-based material modification in transparent solids, and establishes a new scientific aspect of strong-field optics, namely, focal volume optics for composite structuring transparent solids.

Research on Vibration Control of FAST Feed Cabin Based on Active Mass Damper

In this paper, an effective active vibration control method was investigated to further improve the positioning accuracy of the Five-hundred-meter Aperture Spherical radio Telescope (FAST) feed cabin. The actual operation data of FAST was collected to analyze the vibration characteristics of the feed cabin in multiple directions. A simplified model of the cabin-cable system was established to evaluate the effects of a mass damper on different vibration frequencies and modes. On this basis, an active mass damper system and control system were designed for the cabin with multiple degrees of freedom and modal variation characteristics. Theoretical calculation and simulation proved that it has a significant effect on improving the damping of the cabin-cable system and suppressing the vibration of the FAST feed cabin.

Design of a Bionic Spider Robot with a Two-Degrees-of-Freedom Leg Structure and Body Frame

Spiders have unique biological characteristics and excellent maneuverability, making them an ideal model for bionic robot design. However, traditional bionic spider robot designs usually have multiple degrees of freedom and confront many challenges. These challenges include complex control requirements, higher energy consumption, larger size and weight, higher risk of failure, and higher cost. This study proposes a leg design with two degrees of freedom to reduce its control and manufacturing costs. It can better control leg movement and improve leg force through a multi-link mechanism and a dual-motor system. In addition, the triangular gait and hexagonal body structure align the weight of the body with the support point, thereby enhancing stability. This study offers a comprehensive and organized approach to bio-inspired robot design, providing a valuable reference for future bionic robot development.

Extended influence coefficient method for meshing stiffness evaluation of spur gears considering rotor flexibility

Rotor-supported gears are applied in transmission systems, and the rotor flexiblility leads to the misalignment of the gear pair with multiple degrees of freedom, which ultimately leads to the decrease of meshing stiffness. To evaluate the meshing stiffness of rotor-supported gears, the extended influence coefficient method (EICM) is proposed in this paper. Firstly, the gear contact position adjustment under misalignment condition is carried out. Then, the extended influence coefficients of bending, shearing, axial compression, Hertzian contact and fillet foundation deformation of gears are derived to obtain the extended influence coefficient matrix. Afterward, the load-deformation equations under different contact states are obtained, and the meshing stiffness is calculated. Subsequently, a cantilever rotor-gear coupling dynamic model is established by the rigid body element-extended influence coefficient method (RBE-EICM), and the dynamic meshing stiffness considering rotor flexibility is obtained. The accuracy of EICM and RBE-EICM is verified by comparison with finite element method, literature methods and experimental data, respectively. Finally, the effects of supporting layout, input torque and rotor diameter on the dynamic characteristics of cantilever rotor-supported gears are discussed.

Human motor learning dynamics in high-dimensional tasks.

Conventional approaches to enhance movement coordination, such as providing instructions and visual feedback, are often inadequate in complex motor tasks with multiple degrees of freedom (DoFs). To effectively address coordination deficits in such complex motor systems, it becomes imperative to develop interventions grounded in a model of human motor learning; however, modeling such learning processes is challenging due to the large DoFs. In this paper, we present a computational motor learning model that leverages the concept of motor synergies to extract low-dimensional learning representations in the high-dimensional motor space and the internal model theory of motor control to capture both fast and slow motor learning processes. We establish the model's convergence properties and validate it using data from a target capture game played by human participants. We study the influence of model parameters on several motor learning trade-offs such as speed-accuracy, exploration-exploitation, satisficing, and flexibility-performance, and show that the human motor learning system tunes these parameters to optimize learning and various output performance metrics.

A Review of Linear Compressor Vibration Isolation Methods

Linear compressors exhibit high compression efficiency and low noise characteristics, showcasing broad application prospects in various fields such as aerospace, medicine, household appliances, and more. However, due to the complexity of their structures and operation, the issue of vibration isolation in linear compressors has long been a research challenge within the industry. Addressing this challenge, this paper provides an overview of vibration isolation optimization methods for linear compressors. It delves into the discussion of different vibration sources in linear compressors and their respective measurement techniques. By integrating both single degree of freedom (SDOF) and multiple degree of freedom (MDOF) vibration isolation models, this paper describes both active and passive vibration isolation methods tailored to linear compressors. Furthermore, a feasible optimization approach is proposed. Finally, the paper offers insights into the developmental potential and feasibility of vibration energy recovery strategies.

An Adaptive Chirp Mode Decomposition-Based Method for Modal Identification of Time-Varying Structures

Modal parameters are inherent characteristics of civil structures. Due to the effect of environmental factors and ambient loads, the physical and modal characteristics of a structure tend to change over time. Therefore, the effective identification of time-varying modal parameters has become an essential topic. In this study, an instantaneous modal identification method based on an adaptive chirp mode decomposition (ACMD) technique was proposed. The ACMD technique is highly adaptable and can accurately estimate the instantaneous frequencies of a structure. However, it is important to highlight that an initial frequency value must be selected beforehand in ACMD. If the initial frequency is set incorrectly, the resulting instantaneous frequencies may lack accuracy. To address the aforementioned problem, the Welch power spectrum was initially developed to extract a high-resolution time–frequency distribution from the measured signals. Subsequently, the time–frequency ridge was identified based on the maximum energy position in the time–frequency distribution plot, with the frequencies associated with the time–frequency ridge serving as the initial frequencies. Based on the initial frequencies, the measured signals with multiple degrees of freedom could be decomposed into individual time-varying components with a single degree of freedom. Following that, the instantaneous frequencies of each time-varying component could be calculated directly. Subsequently, a sliding window principal component analysis (PCA) method was introduced to derive instantaneous mode shapes. Finally, vibration data collected under various operational scenarios were used to validate the proposed method. The results demonstrated the effective identification of time-varying modal parameters in real-world civil structures, without missing modes.

Design and Performance Evaluation of a Novel Vascular Interventional Surgery Robot

Introduction: Minimally invasive interventional surgical robots are used as delivery tools to assist healthcare professionals with medical devices such as micro guidewires and microcatheters during surgical treatment of cardiovascular and cerebrovascular obstruction, thus reducing surgical fatigue and radiation for healthcare professionals. Method: In this paper, a new vascular interventional surgical robot with multiple degrees of freedom is designed, its mechanism principle and movement mode is discussed in detail, and a prototype prototype is fabricated to make it simulate and reproduce the doctor's hand movements. Results: Through Abaqus simulation and platform experiments, the performance of the surgical robot is evaluated and analyzed from the perspectives of micro guidewire delivery displacement accuracy and radial clamping force for its high accuracy, high reliability, and safety. Conclusion: The results demonstrate that its surgical robot meets the requirements of providing vessel wall overload protection while the microcatheter delivery positioning accuracy error is less than 1 mm.

Online control parameter optimization design for multi-machine coordinated loading system of hazardous substances

To address the parameter instability issues in hazardous materials handling during multi-machine loading and unloading operations, we propose a Full-Scale Smart Parameter Optimization Control (FSPOC) system specifically designed for multi-machine coordination. This system leverages a novel fish scale prediction algorithm tailored for cooperative multi-machine environments. Initially, the fish scale prediction algorithm, inspired by bionic fish scales, is developed to predict future system behavior by analyzing historical data. Building on this algorithm, we introduce a disturbance cancellation control theorem and design a parameter optimization controller to enhance stability in high-dimensional nonlinear spaces. The FSPOC method is then applied to a multi-machine cooperative system, enabling online distributed parameter optimization for complex systems with multiple degrees of freedom. The effectiveness of the proposed method was validated through simulations, where it was compared with two other optimization techniques: Genetic Algorithm-based PID (GAPID) and Chaotic Atomic Search Algorithm-based PID (CHASO). The simulation results confirm the superiority of the FSPOC method.

Correlating light fields through disordered media across multiple degrees of freedom

Speckle patterns are inherent features of coherent light propagation through complex media. As a result of interference, they are sensitive to multiple experimental parameters such as the configuration of disorder or the propagating wavelength. Recent developments in wavefront shaping have made it possible to control speckle pattern statistics and correlations, for example using the concept of the transmission matrix. In this article, we address the problem of correlating scattered fields across multiple degrees of freedom. We highlight the common points between the specific techniques already demonstrated, and we propose a general framework based on the singular value decomposition of a linear combination of multiple transmission matrices. Following analytical predictions, we experimentally illustrate the technique on spectral and temporal correlations, and we show that both the amplitude and the phase of the field correlations can be tuned. Our work opens up new perspectives in speckle correlation manipulation, with potential applications in coherent control. Published by the American Physical Society 2024

Structural state nonlinearity-based design and modification formulae of inerter-based systems

As structural safety emerges as a paramount concern and with the advancement in vibration control technology, a notable gap persists in accurately simulating structural state nonlinearity, especially within the field of inerter-based seismic control technology. Dealing with the need to upgrade the seismic performance of practical nonlinear structures, this study proposes a structural state nonlinearity-based design method for inerter-incorporated civil structures by incorporating the target seismic performance, structural nonlinearity level, and ground motion effects. By establishing mechanical models of inerter-based systems with straightforward parameters and a prototypical bilinear model for the primary structure, governing equations for inerter-incorporated structures were derived. Later, structural state nonlinearity-based design method for inerter-based systems, including optimization criteria and parameter distribution pattern, is elaborated. Simultaneously, this study also provides structural state nonlinearity-based design curves and modification formulae related to structural state nonlinearity and peak ground acceleration of earthquake. Validated using a 10-story multiple-degree-of-freedom (MDOF) structure subjected to earthquakes, the results highlight the effectiveness of the method, emphasizing its potential in controlling seismic responses of structures within the predetermined performance target. In addition, the absolute acceleration mitigation effect of inerter-based systems is investigated. The efficiency and robustness of the proposed method are also verified under near-fault and far-fault earthquakes. In essence, this research pioneers an approach in inerter-based design, bridging structural state nonlinearity, and potentially reshaping seismic control strategies to align with diverse structural states.

How Multifunctioning Joints Produce Highly Agile Limbs in Animals with Lessons for Robotics.

This paper reviews how multifunctioning joints produce highly agile limbs in animals with lessons for robotics. One of the key reasons why animals are so fast and agile is that they have multifunctioning joints in their limbs. The multifunctioning joints lead to a high degree of compactness which then leads to a host of benefits such as low mass, low moment of inertia and low drag. This paper presents three case studies of multifunctioning joints-the human wrist joint, knee joint and foot joints-in order to identify how multifunctioning is achieved and what lessons can be learned for robotics. It also reviews the multifunctioning nature of muscle which plays an important role in joint actuation. A key finding is that multifunctioning is achieved through various means: multiple degrees of freedom, multifunctioning parts, over-actuation and reconfiguration. In addition, multifunctioning is achieved through highly sophisticated layouts with high levels of integration and fine-tuning. Muscle also makes an important contribution to animal agility by performing multiple functions including providing shape, protection and heat. The paper reviews progress in achieving multifunctioning in robot joints particularly for the wrist, knee and foot. Whilst there has been some progress in creating multifunctioning robotic joints, there is still a large gap between the performance of animal and robotic joints. There is an opportunity to improve the agility of robots by using multifunctioning to reduce the size and mass of robotic joints.

Nonequilibrium relaxation of soft responsive colloids.

Stimuli-responsive macromolecules display large conformational changes during their dynamics, sometimes switching between states. Such a multi-stability is useful for the development of soft functional materials. Here, we introduce a mean-field dynamical density functional theory for a model of responsive colloids to study the nonequilibrium dynamics of a colloidal dispersion in time-dependent external fields, with a focus on the coupling of translational and conformational dynamics during their relaxation. Specifically, we consider soft Gaussian particles with a bimodal size distribution between two confining walls with time-dependent (switching-on and off) external gravitational and osmotic fields. We find a rich relaxation behavior of the systems in excellent agreement with particle-based Brownian dynamics computer simulations. In particular, we find time-asymmetric relaxations of integrated observables (wall pressures, mean size, and liquid center-of-mass) for activation/deactivation of external potentials, respectively, which are tunable by the ratio of translational and conformational diffusion time scales. Our work thus paves the way for studying the nonequilibrium relaxation dynamics of complex soft matter with multiple degrees of freedom and hierarchical relaxations.

Inverse kinematic solution and singularity avoidance using a deep deterministic policy gradient approach

<p>The robotic arm emerges as a subject of paramount significance within the industrial landscape, particularly in addressing the complexities of its kinematics. A significant research challenge lies in resolving the inverse kinematics of multiple degree of freedom (M-DOF) robotic arms. The inverse kinematics of M-DOF robotic arms pose a challenging problem to resolve, thus it involves consideration of singularities which affect the arm robot movement. This study aims a novel approach utilizing deep reinforcement learning (DRL) to tackle the inverse kinematic problem of the 6-DOF PUMA manipulator as a representative case within the M-DOF manipulator. The research employs Jacobian matrix for the kinematics system that can solve the singularity, and deep deterministic policy gradient (DDPG) as the kinematics solver. This chosen technique offers enhancing speed and ensuring stability. The results of inverse kinematic solution using DDPG were experimentally validated on a 6-DOF PUMA arm robot. The DDPG successfully solves inverse kinematic solution and avoids the singularity with 1,000 episodes and yielding a commendable total reward of 1,018.</p>

Aerodynamic optimization of multi-stage axial turbine based on pre-screening strategy and directly manipulated free-form deformation

To address the challenges of multiple design variables, long evaluation times, and poor global search capability of traditional surrogate-assisted algorithms that rely on the complete substitution of accurate function evaluations in the turbine aerodynamic optimization process, a pre-screening surrogate-assisted elitist preservation genetic algorithm (pre-SAEGA) optimizer is proposed. Pre-screening strategy in the pre-SAEGA can screen samples instead of directly estimating them, thereby reducing expensive evaluations in each generation. The directly manipulated free-form deformation (DFFD) method is applied to parameterized multi-stage axial turbines, and multi-degree-of-freedom flexible control is realized. Combining the pre-SAEGA with the DFFD method, a data-driven multi-stage axial turbine optimization platform is established. A two-stage axial turbine is the research object, and 44 design variables are selected for the combined optimization design of flow path and blade rows. The results show that the isentropic efficiency and flow rate improve by 1.33 % and 1.81 % respectively, and the pressure ratio decreases by 0.47 % at the turbine design point. The presented optimization platform not only improves the aerodynamic optimization effect but also significantly reduces the number of design variables and real evaluation samples, making it suitable for solving multi-stage turbine optimization problems with multiple degrees of freedom.