Biomimetics最新文献

Future humanoid robots will be widely deployed in our daily lives. Motion planning and control in an unstructured, confined, and human-centered environment utilizing dexterity and a cooperative ability of dual-arm robots is still an open issue. We propose a globally guided dual-arm reactive motion controller (GGDRC) that combines the strengths of global planning and reactive methods. In this framework, a global planner module with a prospective task horizon provides feasible guidance in a Cartesian space, and a local reactive controller module addresses real-time collision avoidance and coordinated task constraints through the exploitation of dual-arm redundancy. GGDRC extends the start-of-the-art optimization-based reactive method for motion-restricted dynamic scenarios requiring dual-arm cooperation. We design a pick-handover-place task to compare the performances of these two methods. Results demonstrate that GGDRC exhibits accurate collision avoidance precision (5 mm) and a high success rate (84.5%).

In order to improve the walking stability of a biped robot in multiple scenarios and reduce the complexity of the Central Pattern Generator (CPG) model, a new CPG walking controller based on multivariate linear mapping was proposed. At first, in order to establish a dynamics model, the lower limb mechanical structure of the biped robot was designed. According to the Lagrange and angular momentum conservation method, the hybrid dynamic model of the biped robot was established. The initial value of the robot's passive walking was found by means of Poincaré mapping and cell mapping methods. Then, a multivariate linear mapping model was established to form a new lightweight CPG model based on a Hopf oscillator. According to the parameter distribution of the new CPG model, a preliminary parameter-tuning idea was proposed. At last, the joint simulation of MATLAB and V-REP shows that the biped robot based on the new CPG control has a stable periodic gait in flat and uphill scenes. The proposed method could improve the stability and versatility of bipedal walking in various environments and can provide general CPG generation and a tuning method reference for robotics scholars.

Bionic multi-legged robots with flexible bodies embody human ingenuity in imitating, learning, and exploring the natural world. In contrast to rigid-body robots, these robots with flexible bodies exhibit superior locomotive capabilities. The flexible body of the robot not only boosts the moving speed and walking stability but also enhances adaptability across complex terrains. This article focuses on the innovative design of flexible bodies. Firstly, the structural designs, including artificial spines and single/multi-axis articulation mechanisms, are outlined systematically. Secondly, the enhancement of robotic motion by flexible bodies is reviewed, examining the impact that body degrees of freedom, stiffness, and coordinated control between the body and limbs have on robotic motion. Thirdly, existing robotic control methods, organized by control architectures, are comprehensively overviewed in this article. Finally, the application prospects of bionic multi-legged robots with flexible bodies are offered, and the challenges that may arise in their future development are listed. This article aims to serve as a reference for bionic robot research.

The inverse kinematics of robotic manipulators involves determining an appropriate joint configuration to achieve a specified end-effector position. This problem is challenging because the inverse kinematics of manipulators are highly nonlinear and complexly coupled. To address this challenge, the bald eagle search optimization algorithm is introduced. This algorithm combines the advantages of evolutionary and swarm techniques, making it more effective at solving nonlinear problems and improving search efficiency. Due to the tendency of the algorithm to fall into local optima, the Lévy flight strategy is introduced to enhance its performance. This strategy adopts a heavy-tailed distribution to generate long-distance jumps, thereby preventing the algorithm from becoming trapped in local optima and enhancing its global search efficiency. The experiments first evaluated the accuracy and robustness of the proposed algorithm based on the inverse kinematics problem of manipulators, achieving a solution accuracy of up to 10-18 m. Subsequently, the proposed algorithm was compared with other algorithms using the CEC2017 test functions. The results showed that the improved algorithm significantly outperformed the original in accuracy, convergence speed, and stability. Specifically, it achieved over 70% improvement in both standard deviation and mean for several test functions, demonstrating the effectiveness of the Lévy flight strategy in enhancing global search capabilities. Furthermore, the practicality of the proposed algorithm was verified through two real engineering optimization problems.

Geckos are renowned for their exceptional climbing abilities, enabled by their specialized feet with hairy toes that attach to surfaces using van der Waals forces. Inspired by these capabilities, various gecko-like robots have been developed for high-risk applications, such as search and rescue. While most research has focused on adhesion mechanisms, the gecko's tail also plays a critical role in maintaining balance and stability. In this study, we systematically explore the impact of tail dynamics on the climbing performance of gecko-inspired robots through both simulation and experimental analysis. We developed a dynamic climbing simulation system that models the robot's specialized attachment devices and predicts contact failures. Additionally, an adjustable-angle force measurement platform was constructed to validate the simulation results. Our findings reveal the significant influence of the tail on the robot's balance, stability, and maneuverability, providing insights for further optimizing climbing robot performance.

Nanocellulose is considered a promising and sustainable biomaterial, with excellent properties of biorenewability with improved mechanical properties. As a unique natural biopolymer, it has been applied to many different industries, where efficient and environmentally friendly productions are in demand. For the first time, ferns from the class Polypodiopsida were used for the isolation of cellulose fibers, which was performed using a chemo-mechanical method. As chemical treatment plays a crucial role in the isolation of nanocellulose, it affects the efficiency of the extraction process, as well as the properties of the resulting nanocellulose. Therefore, mechanical fibrillation was performed via grinding, while the chemical process consisted of three different treatments: alkali treatment, bleaching, and acid hydrolysis. In three different experiments, each treatment was separately prolonged to investigate the differing properties of isolated nanocellulose. Structural analysis and morphological analysis were investigated by SEM, EDS, FT-IR, and DLS. The thermal stability of cellulose fibers was investigated by TGA/DSC. The morphology of obtained nanocellulose was confirmed via SEM analysis for all samples, with particles ranging from 20 nm up to 600 nm, while the most consistent sizes were observed for NC3, ranging from 20 to 60 nm. FT-IR spectra showed prominent absorption peaks corresponding to cellulose, as well as the absence of absorption peaks, corresponding to lignin and hemicellulose. The EDS confirmed the elemental purity of nanocellulose, while TGA/DSC indicated higher thermal stability of nanocellulose, compared to untreated fern, which started to degrade earlier than nanocellulose. Such characteristics with unique properties make nanocellulose a versatile biomaterial for the industrial production of cellulosic materials.

Dung beetle leg joints exhibit a remarkable capacity to support substantial loads, which is a capability significantly influenced by their surface microstructure. The exploration of biomimetic designs inspired by the surface microstructure of these joints holds potential for the development of efficient self-locking structures. However, there is a notable absence of research focused on the surface microstructure of dung beetle leg joints. In this study, we investigated the structural characteristics of the surface microstructures present in dung beetle leg joints, identifying the presence of fish-scale-like, brush-like, and spike-like microstructures on the tibia and femur. Utilizing these surface microstructural characteristics, we designed a self-locking structure that successfully demonstrated functionality in both the rotational direction of the structure and self-locking in the reverse direction. At a temperature of 20 °C, the biomimetic closure featuring a self-locking mechanism was capable of generating a self-locking force of 18 N. The bionic intelligent joint, characterized by its unique surface microstructure, presents significant potential applications in aerospace and various engineering domains, particularly as a critical component in folding mechanisms. This research offers innovative design concepts for folding mechanisms, such as those utilized in satellite solar panels and solar panels for asteroid probes.

This study addresses the problem that the traditional method is not effective in improving the adsorption performance of vacuum suckers. From the perspective of bionics, the adsorption performance of bionic suckers based on the excellent adsorption of the abalone abdominal foot was studied. A bionic sucker was designed by extracting the sealing ring structure of the abdominal foot tentacle. The bionic sucker was subjected to tensile experiments using an orthogonal experimental design, and the adsorption of the bionic sucker was simulated and analyzed to explore its adsorption mechanism. The results show that the primary and secondary factors affecting the adsorption of the sucker are the number of sealing rings, the width of sealing rings and the spacing of sealing rings. At 60% vacuum, the bionic sucker with two sealing rings, a 1.5 mm sealing ring width and 3 mm sealing ring spacing has the largest adsorption force, and its maximum adsorption force is 15.8% higher than that of the standard sucker. This study shows that the bionic sucker design can effectively improve the adsorption performance of the sucker. The bionic sucker had a different stress distribution on the sucker bottom, which resulted in greater Mises stress in the sealing ring and the surrounding area, while the Mises stress in the central area of the sucker was smaller.

Kinematics, kinetics and biomechanics of human gait are widely investigated fields of research. The biomechanics of locomotion have been described as characterizing muscle activations and synergistic control, i.e., spatial and temporal patterns of coordinated muscle groups and joints. Both kinematic synergies and muscle synergies have been extracted from locomotion data, showing that in healthy people four-five synergies underlie human locomotion; such synergies are, in general, robust across subjects and might be altered by pathological gait, depending on the severity of the impairment. In this work, for the first time, we apply the mixed matrix factorization algorithm to the locomotion data of 15 healthy participants to extract hybrid kinematic-muscle synergies and show that they allow us to directly link task space variables (i.e., kinematics) to the neural structure of muscle synergies. We show that kinematic-muscle synergies can describe the biomechanics of motion to a better extent than muscle synergies or kinematic synergies alone. Moreover, this study shows that at a functional level, modular control of the lower limb during locomotion is based on an increased number of functional synergies with respect to standard muscle synergies and accounts for different biomechanical roles that each synergy may have within the movement. Kinematic-muscular synergies may have impact in future work for a deeper understanding of modular control and neuro-motor recovery in the medical and rehabilitation fields, as they associate neural and task space variables in the same factorization. Applications include the evaluation of post-stroke, Parkinson's disease and cerebral palsy patients, and for the design and development of robotic devices and exoskeletons during walking.

This study aimed to identify whether the combined use of functional electrical stimulation (FES) reduces the motor torque of a gait exercise rehabilitation robot in spinal cord injury (SCI) and to verify the effectiveness of the developed automatic assist level adjustment in people with paraplegia. Acute and chronic SCI patients (1 case each) performed 10 min of gait exercises with and without FES using a rehabilitation robot. Reinforcement learning was used to adjust the assist level automatically. The maximum torque values and assist levels for each of the ten walking cycles when walking became steady were averaged and compared with and without FES. The motor's output torque and the assist level were measured as outcomes. The assist level adjustment allowed both the motor torque and assist level to decrease gradually to a steady state. The motor torque and the assist levels were significantly lower with the FES than without the FES under steady conditions in both cases. No adverse events were reported. The combined use of FES attenuated the motor torque of a gait exercise rehabilitation robot for SCI. Automatic assistive level adjustment is also useful for spinal cord injuries.