Haptic guidance has been studied to promote sensory-based decision making and motor learning using rigid-body haptic robots, however at the expense of complex intertwined byproducts of motor skill learning and navigat...
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Optimal route planning for autonomous robots is a crucial element of contemporary agriculture, especially for activities like spraying and pollination. This paper presents a Graph Convolutional Network (GCN) model esp...
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In this article, the chaotic Brillouin phase-gain dual-parametric spectrum (BDS) is measured for the first time, which can realize high-accuracy and large-range dynamic strain demodulation in chaotic Brillouin optical...
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Multi-agent path finding (MAPF) is an essential issue for warehouse automation, where multiple agents plan collision-free paths from the start to goal positions. Reinforcement learning (RL) has been employed to develo...
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Multi-agent path finding (MAPF) is an essential issue for warehouse automation, where multiple agents plan collision-free paths from the start to goal positions. Reinforcement learning (RL) has been employed to develop partially observable distributed MAPF methods that can be scaled to any number of agents. However, existing RL-based MAPF methods still have some limitations in handling redundant information and avoiding deadlock, resulting in a low success rate or longer makespan. This paper proposes a Priority-aware Communication & Experience learning method (PCE), which combines RL with a novel priority-aware multi-agent communication and a new priority-aware deadlock experience replay to tackle this challenge. To be specific, our innovation encompasses two-fold. Our proposed communication mechanism aims to handle redundant information, which establishes a dynamic communication topology based on agents' priorities and proposes a two-head priority-aware graph attention network to aggregate information. In order to help the agent avoid deadlock, we prioritize the expert experience that solves the deadlock when performing experience replay. We conduct multiple simulation experiments on warehouse-like structured grid maps. Compared with the state-of-the-art RL-based MAPF methods, PCE performs significantly better with a higher success rate and lower makespan in small and large MAPF and higher average throughput in the lifelong MAPF, which can further improve the efficiency of warehouse automation. Finally, we validate PCE using three Turtlebot3-Burger robots, which shows that PCE can be applied in real warehouse automation scenarios. IEEE
With the increasing requirement for agile and efficient controllers in safety-critical scenarios, controllers that exhibit both agility and safety are attracting attention, especially in the aerial robotics domain. Th...
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Four-wheel drive Mecanum robots have gained attention due to their ability to move in all directions, which allows them to work in tight and complex environments. For this reason, ensuring precise control of these rob...
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CircRNA-disease association(CDA) can provide a new direction for the treatment of diseases. However,traditional biological experiment is time-consuming and expensive, this urges us to propose the reliable computationa...
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CircRNA-disease association(CDA) can provide a new direction for the treatment of diseases. However,traditional biological experiment is time-consuming and expensive, this urges us to propose the reliable computational model to predict the associations between circRNAs and diseases. And there is existing more and more evidence indicates that the combination of multi-biomolecular information can improve the prediction accuracy. We propose a novel computational model for CDA prediction named MBCDA, we collect the multi-biomolecular information including circRNA, disease, miRNA and lncRNA based on 6 databases, and construct three heterogeneous network among them, then the multi-heads graph attention networks are applied to these three networks to extract the features of circRNAs and diseases from different views, the obtained features are put into variational graph auto-encoder(VGAE) network to learn the latent distributions of the nodes, a fully connected neural network is adopted to further process the output of VGAE and uses sigmoid function to obtain the predicted probabilities of circRNA-disease *** a result, MBCDA achieved the values of AUC and AUPR under 5-fold cross-validation of 0.893 and 0.887. MBCDA was applied to the analysis of the top-25 predicted associations between circRNAs and diseases, these experimental results show that our proposed MBCDA is a powerful computational model for CDA prediction.
In this paper,a visual servoing approach is developed to capture the docking rings of tumbling non-cooperative satellites with a space *** primary challenge addressed is the potential for the docking ring to leave the...
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In this paper,a visual servoing approach is developed to capture the docking rings of tumbling non-cooperative satellites with a space *** primary challenge addressed is the potential for the docking ring to leave the monocular camera’s field-of-view as the manipulator approaches the target,due to the ring’s large *** solve this issue,a two-phase visual servoing scheme combining a monocular camera and a three-line structured light vision system is *** an effort to augment the success rate and safety of capture operations,several constraints are formulated,encompassing manipulator’s kinematics,monocular camera’s field-of-view,obstacle avoidance,structured light’s breakpoints and smooth ***,a nonlinear model predictive controller is proposed to manage these constraints in real-time and regulate the *** models are established based on image moments and pose for each phase,selecting these features as visual feedback to simplify the formulation of servo constraints and avoid the complex circle-based pose ***,to ensure unbiased predictions,the model disturbances arising from the imprecise estimation of target motion parameter are observed using an extended Kalman filter,which are then incorporated into the predictive control *** simulation results demonstrate the effectiveness of this scheme.
This study focuses on addressing kinematic singularity analysis and avoidance issues for a space station remote manipulator system(SSRMS)-type reconfigurable space *** manipulator is equipped with a non-spherical wris...
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This study focuses on addressing kinematic singularity analysis and avoidance issues for a space station remote manipulator system(SSRMS)-type reconfigurable space *** manipulator is equipped with a non-spherical wrist and two lockable passive telescopic links(LPTLs),which enable it to have both active revolute and passive prismatic joints and operate in two distinct *** begin with the kinematic singularity analysis,the study derives the differential kinematic equations for the manipulator and identifies the dominant Jacobian matrix that causes ***,an in-depth analysis of singularities from multiple perspectives is ***,a kinematic singularity map method is proposed to capture the distribution of singularities within the reachable ***,the influence of the two LPTLs on singularities is thoroughly ***,a new method based on the matrix rank equivalence principle is introduced to determine singularity conditions,enabling the identification of all the singular configurations for the SSRMS-type reconfigurable ***,this method significantly reduces computational complexity,and the singularity conditions obtained have more concise *** the singularity avoidance problem,a novel method is developed,which simultaneously addresses the requirements of real-time performance,high precision,and the avoidance of both kinematic singularities and joint limit *** from these excellent properties,the proposed method can effectively resolve the singularity issues encountered separately by the SSRMS-type reconfigurable manipulator in its two operational *** typical simulations validate the utility of all the proposed methods.
To solve the problem of undesired relative motion of human-machine interaction positions caused by misalignment of the human-machine joints rotation axis of the knee exoskeleton,this study designed an adaptive knee ex...
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To solve the problem of undesired relative motion of human-machine interaction positions caused by misalignment of the human-machine joints rotation axis of the knee exoskeleton,this study designed an adaptive knee exoskeleton based on a gear-link mechanism(GLM)by considering the human body as a component of the exoskeleton ***,the concept of the wearable area(WA)was proposed,which transformed the operation of aligning the exoskeleton rotation axis with the human knee joint rotation axis into a"face alignment point"in the sagittal plane,reducing the difficulty of aligning the human-machine joint rotation *** the kinematic analysis of GLM,the phenomenon of instantaneous movement of the central axis of the human knee joint was *** on the kinematic model,the WA,velocity transfer ratio,and initial position static stiffness of GLM were *** NSGA-II optimization algorithm was used to optimize the size parameters of GLM,which increased the WA by 18.4%,the average velocity transfer ratio by 4.98%,and the average initial position static stiffness by 6.01%.Finally,the ability of the exoskeleton to absorb movement displacement(MD)was verified through simulation,and the good human-machine kinematic compatibility of the exoskeleton was verified through wearable tests conducted on the initial mechanism principle prototype.
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