A Generative Human-Robot Motion Retargeting Approach Using a Single RGBD Sensor

The goal of human-robot motion retargeting is to let a robot follow the movements performed by a human subject. Typically in previous approaches, the human poses are precomputed from a human pose tracking system, after which the explicit joint mapping strategies are specified to apply the estimated poses to a target robot. However, there is not any generic mapping strategy that we can use to map the human joint to robots with different kinds of configurations. In this paper, we present a novel motion retargeting approach that combines the human pose estimation and the motion retargeting procedure in a unified generative framework without relying on any explicit mapping. First, a 3D parametric human-robot (HUMROB) model is proposed which has the specific joint and stability configurations as the target robot while its shape conforms the source human subject. The robot configurations, including its skeleton proportions, joint limitations, and DoFs are enforced in the HUMROB model and get preserved during the tracking procedure. Using a single RGBD camera to monitor human pose, we use the raw RGB and depth sequence as input. The HUMROB model is deformed to fit the input point cloud, from which the joint angle of the model is calculated and applied to the target robots for retargeting. In this way, instead of fitted individually for each joint, we will get the joint angle of the robot fitted globally so that the surface of the deformed model is as consistent as possible to the input point cloud. In the end, no explicit or pre-defined joint mapping strategies are needed. To demonstrate its effectiveness for human-robot motion retargeting, the approach is tested under both simulations and on real robots which have a quite different skeleton configurations and joint degree of freedoms (DoFs) as compared with the source human subjects

Influence of “J”-Curve Spring Stiffness on Running Speeds of Segmented Legs during High-Speed Locomotion

Both the linear leg spring model and the two-segment leg model with constant spring stiffness have been broadly used as template models to investigate bouncing gaits for legged robots with compliant legs. In addition to these two models, the other stiffness leg spring models developed using inspiration from biological characteristic have the potential to improve high-speed running capacity of spring-legged robots. In this paper, we investigate the effects of “J”-curve spring stiffness inspired by biological materials on running speeds of segmented legs during high-speed locomotion. Mathematical formulation of the relationship between the virtual leg force and the virtual leg compression is established. When the SLIP model and the two-segment leg model with constant spring stiffness and with “J”-curve spring stiffness have the same dimensionless reference stiffness, the two-segment leg model with “J”-curve spring stiffness reveals that (1) both the largest tolerated range of running speeds and the tolerated maximum running speed are found and (2) at fast running speed from 25 to 40/92 m s−1 both the tolerated range of landing angle and the stability region are the largest. It is suggested that the two-segment leg model with “J”-curve spring stiffness is more advantageous for high-speed running compared with the SLIP model and with constant spring stiffness

Dynamic Non-Rigid Objects Reconstruction with a Single RGB-D Sensor

This paper deals with the 3D reconstruction problem for dynamic non-rigid objects with a single RGB-D sensor. It is a challenging task as we consider the almost inevitable accumulation error issue in some previous sequential fusion methods and also the possible failure of surface tracking in a long sequence. Therefore, we propose a global non-rigid registration framework and tackle the drifting problem via an explicit loop closure. Our novel scheme starts with a fusion step to get multiple partial scans from the input sequence, followed by a pairwise non-rigid registration and loop detection step to obtain correspondences between neighboring partial pieces and those pieces that form a loop. Then, we perform a global registration procedure to align all those pieces together into a consistent canonical space as guided by those matches that we have established. Finally, our proposed model-update step helps fixing potential misalignments that still exist after the global registration. Both geometric and appearance constraints are enforced during our alignment; therefore, we are able to get the recovered model with accurate geometry as well as high fidelity color maps for the mesh. Experiments on both synthetic and various real datasets have demonstrated the capability of our approach to reconstruct complete and watertight deformable objects

Generating Human-Like Velocity-Adapted Jumping Gait from sEMG Signals for Bionic Leg’s Control

In the case of dynamic motion such as jumping, an important fact in sEMG (surface Electromyogram) signal based control on exoskeletons, myoelectric prostheses, and rehabilitation gait is that multichannel sEMG signals contain mass data and vary greatly with time, which makes it difficult to generate compliant gait. Inspired by the fact that muscle synergies leading to dimensionality reduction may simplify motor control and learning, this paper proposes a new approach to generate flexible gait based on muscle synergies extracted from sEMG signal. Two questions were discussed and solved, the first one concerning whether the same set of muscle synergies can explain the different phases of hopping movement with various velocities. The second one is about how to generate self-adapted gait with muscle synergies while alleviating model sensitivity to sEMG transient changes. From the experimental results, the proposed method shows good performance both in accuracy and in robustness for producing velocity-adapted vertical jumping gait. The method discussed in this paper provides a valuable reference for the sEMG-based control of bionic robot leg to generate human-like dynamic gait

Towards Human-like Walking with Biomechanical and Neuromuscular Control Features: Personalized Attachment Point Optimization Method of Cable-Driven Exoskeleton

The cable-driven exoskeleton can avoid joint misalignment, and is substantial alterations in the pattern of muscle synergy coordination, which arouse more attention in recent years to facilitate exercise for older adults and improve their overall quality of life. This study leverages principles from neuroscience and biomechanical analysis to select attachment points for cable-driven soft exoskeletons. By extracting key features of human movement, the objective is to develop a subject-specific design methodology that provides precise and personalized support in the attachment points optimization of cable-driven exoskeleton to achieve natural gait, energy efficiency, and muscle coordination controllable in the domain of human mobility and rehabilitation. To achieve this, the study first analyzes human walking experimental data and extracts biomechanical features. These features are then used to generate trajectories, allowing better natural movement under complete cable-driven exoskeleton control. Next, a genetic algorithm-based method is employed to minimize energy consumption and optimize the attachment points of the cable-driven system. This process identifies connections that are better suited for the human model, leading to improved efficiency and natural movement. By comparing the calculated elderly human model driven by exoskeleton with experimental subject in terms of joint angles, joint torques and muscle forces, the human model can successfully replicate subject movement and the cable output forces can mimic human muscle coordination. The optimized cable attachment points facilitate more natural and efficient collaboration between humans and the exoskeleton, making significant contributions to the field of assisting the elderly in rehabilitation

High-Quality Fiber Bragg Gratings Inscribed by Femtosecond Laser Point-by-Point Technology

We experimentally studied the inscription of fiber Bragg gratings by using femtosecond (fs) laser point-by-point (PbP) technology. The effects of the focusing geometry, grating order, laser energy and grating length on the spectral characteristics of the PbP FBG were investigated. After optimizing these parameters, a high-quality first-order PbP FBG with a reflectivity > 99.9% (i.e., Bragg resonance attenuation of 37.7 dB) and insertion loss (IL) of 0.03 dB was successfully created. Moreover, taking advantage of the excellent flexibility of the fs laser PbP technology, high-quality FBGs with various Bragg wavelengths ranging from 856 to 1902.6 nm were inscribed. Furthermore, wavelength-division-multiplexed (WDM) FBG arrays consisting of 10 FBGs were rapidly constructed. Additionally, a Fabry-Perot cavity was realized by using two high-quality FBGs, and its birefringence could be reduced from 3.04 × 10−5 to 1.77 × 10−6 by using a slit beam shaping-assisted femtosecond laser PbP technology. Therefore, such high-quality FBGs are promising to improve the performance of optical fiber sensors, lasers and communication devices

An approach to a web-based flexible workflow modeling

The effective implementation of workflow system in manufacture enterprises enables the enterprises to achieve the benefits associated with the integration, automation and management of their business process. The conventional workflow model based approaches hinder the change of workflow logic flexibly. These approaches face difficulties in satisfying the changing market demands, meeting the demands from intensifying market competition, and adopting new information technology development. After the analysis of the demand for a flexible workflow modelling approach and the characteristics of workflow flexibility, a dynamic workflow modelling framework based on a directed graph theory is proposed in this paper to model the flexible workflow. The key elements of the framework are explained and the modelling approach is described. Using the approach, the changeable business process can be modelled flexibly and concisely without the need of redefinition of workflow model. Finally the paper describes the implementation of the flexible workflow model using a Web-based flexible customer service system

Dynamic Non-Rigid Objects Reconstruction with a Single RGB-D Sensor

This paper deals with the 3D reconstruction problem for dynamic non-rigid objects with a single RGB-D sensor. It is a challenging task as we consider the almost inevitable accumulation error issue in some previous sequential fusion methods and also the possible failure of surface tracking in a long sequence. Therefore, we propose a global non-rigid registration framework and tackle the drifting problem via an explicit loop closure. Our novel scheme starts with a fusion step to get multiple partial scans from the input sequence, followed by a pairwise non-rigid registration and loop detection step to obtain correspondences between neighboring partial pieces and those pieces that form a loop. Then, we perform a global registration procedure to align all those pieces together into a consistent canonical space as guided by those matches that we have established. Finally, our proposed model-update step helps fixing potential misalignments that still exist after the global registration. Both geometric and appearance constraints are enforced during our alignment; therefore, we are able to get the recovered model with accurate geometry as well as high fidelity color maps for the mesh. Experiments on both synthetic and various real datasets have demonstrated the capability of our approach to reconstruct complete and watertight deformable objects

An Approach to a Web-based Flexible Workflow Modeling

Abstract: The effective implementation of workflow system in manufacture enterprises enables the enterprises to achieve the benefits associated with the integration, automation and management of their business process. But the conventional workflow model based approach hinders the change of workflow logic flexibly. These approaches face difficulties in satisfying the changing market demands, meeting the demands from intensifying market competition, and adopting new information technology development. After the analysis of the demand for a flexible workflow modelling approach and the characteristics of workflow flexibility, a dynamic workflow modelling framework based on a directed graph theory is proposed in this paper to model the flexible workflow, the key elements of the framework are explained and the modelling approach is described. Using the approach, the changeable business process can be modelled flexibly and concisely without the need of redefinition of workflow model. The flexibility of resource allocation in the workflow model is also introduced; finally the paper describes the implementation of the flexible workflow model using a Web-based flexible customer service system

Natural variation in ZmNAC087 contributes to total root length regulation in maize seedlings under salt stress

Abstract Soil salinity poses a significant challenge to crop growth and productivity, particularly affecting the root system, which is vital for water and nutrient uptake. To identify genetic factors that influence root elongation in stressful environments, we conducted a genome-wide association study (GWAS) to investigate the natural variation associated with total root length (TRL) under salt stress and normal conditions in maize seedlings. Our study identified 69 genetic variants associated with 38 candidate genes, among which a specific single nucleotide polymorphism (SNP) in ZmNAC087 was significantly associated with TRL under salt stress. Transient expression and transactivation assays revealed that ZmNAC087 encodes a nuclear-localized protein with transactivation activity. Further candidate gene association analysis showed that non-coding variations in ZmNAC087 promoter contribute to differential ZmNAC087 expression among maize inbred lines, potentially influencing the variation in salt-regulated TRL. In addition, through nucleotide diversity analysis, neutrality tests, and coalescent simulation, we demonstrated that ZmNAC087 underwent selection during maize domestication and improvement. These findings highlight the significance of natural variation in ZmNAC087, particularly the favorable allele, in maize salt tolerance, providing theoretical basis and valuable genetic resources for the development of salt-tolerant maize germplasm