In consideration of the poor locomotion ability of most traditional tensegrity robot, a novel tensegrity hopping robot powered by push-pull electromagnets was proposed with better locomotivity. It is able to conduct s...
An experimental and CFD(Computational Fluid Dynamics) study was conducted on the transient behavior of a rapidly starting centrifugal pump. The transient characteristics of the centrifugal pump in the transient period...
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This paper concerns the identification of continuous-time systems in state-space form that are subject to Lebesgue sampling. Contrary to equidistant (Riemann) sampling, Lebesgue sampling consists of taking measurement...
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This paper concerns the identification of continuous-time systems in state-space form that are subject to Lebesgue sampling. Contrary to equidistant (Riemann) sampling, Lebesgue sampling consists of taking measurements of a continuous-time signal whenever it crosses fixed and regularly partitioned thresholds. The knowledge of the intersample behavior of the output data is exploited in this work to derive an expectation-maximization (EM) algorithm for parameter estimation of the state-space and noise covariance matrices. For this purpose, we use the incremental discrete-time equivalent of the system, which leads to EM iterations of the continuous-time state-space matrices that can be computed by standard filtering and smoothing procedures. The effectiveness of the identification method is tested via Monte Carlo simulations.
The high-quality datasets and generalized network model combined with robust evaluation strategies serve as a significant benchmark for developing new policies for industrial bin-picking. In this paper, we propose the...
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The high-quality datasets and generalized network model combined with robust evaluation strategies serve as a significant benchmark for developing new policies for industrial bin-picking. In this paper, we propose the concept of region-aware grasping, a sim2real cutting-edge system to generate and evaluate 6D poses for robots to pick up novel workpieces from stacked environments. It consists of Region-Aware-Dataset, a large-scale synthetic point cloud grasp dataset; and Semantic-Graspnet, a 6D-wise affordance policy that predicts full 6D grasp pose for stacked workpieces. The introduced Semantic-Graspnet transforms the 6D pose prediction problem into semantic categorization via point cloud encoding and decoding. Meanwhile, we propose a robust evaluation strategy based on pose evaluation and mechanical grasping evaluation, which enhances the robot’s grasping success rate and sorting efficiency. In real industrial tasks, the robot achieves a grasp completion rate of 91.3% in cluttered scenes and 89.2% in densely stacked scenes, demonstrating state-of-the-art results in robotic picking-and-placing applications. Note to Practitioners—This work is inspired by the robotic universal AI technique, which holds an indispensable position in industrial as bin-picking tasks. Leveraging this technology, the robot can proficiently perform picking-and-placing for diverse workpieces. The prior robot grasping policies primarily centered on maximizing the optimization of grasp detection to ensure successful grasping. Nevertheless, limitations still exist regarding efficient datasets, generalized network models, and robust evaluation strategies. Therefore, in order to effectively curtail the development cycle of robot picking-and-placing applications, this paper puts forward a novel region-aware grasping policy for stacked workpieces. We have investigated an autonomous grasp label annotation method and constructed a large-scale synthetic point cloud grasp dataset. Subsequently, a seman
In-flight high-speed object capturing is crucial in nature to improve survival and adaptation to the environment, such as the predation of frogs, leopards, and eagles. Despite its ubiquitousness in nature, capturing f...
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ISBN:
(数字)9798350384574
ISBN:
(纸本)9798350384581
In-flight high-speed object capturing is crucial in nature to improve survival and adaptation to the environment, such as the predation of frogs, leopards, and eagles. Despite its ubiquitousness in nature, capturing fast-moving objects is extremely challenging in engineering implementations. In this paper, we report an ultrafast gripper based on tunable bistable structures. Different from current designs which are only suitable for objects with certain speed ranges once the grippers are fabricated, the working range of object speed of the proposed gripper could be reprogrammed by controlling the sensitivity of the structures. We present the design and fabrication of the proposed gripper in detail. A theoretical model is introduced to construct the energy landscape of the structures and the force response of the gripper when programmed to different states. The results show that in the original state, the gripper is capable of capturing a flying table tennis ball with a high speed of 15 m/s in only 6 ms. When the proposed gripper is controlled to the ultra-sensitive state, a flying ball with only 1 m/s could also be captured. This work broadens the frontiers of in-flight capturing design, and we envision broader promising applications.
This paper presents passivity-based control of nonlinear systems with retarded delays in the state. To this end, we first show that the standard passivity concept can naturally be generalized to time-delay systems, wh...
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This paper presents passivity-based control of nonlinear systems with retarded delays in the state. To this end, we first show that the standard passivity concept can naturally be generalized to time-delay systems, which readily implies that a feedback interconnection (with or without communication delays) of passive time-delay systems is also passive. Then, we propose a storage functional for passivity analysis and further use it for stability analysis of controlled-passive time-delay systems. In particular, invoking an invariance principle for retarded functional differential equations, we show that a passive time-delay system can always be stabilized by a static output feedback controller under a delayed version of the zero-state detectability assumption.
Field-emission electric propulsion is an electrostatic space electric propulsion technology that offers various advantageous features including efficient design, high specific impulse, and versatile thrust capabilitie...
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Field-emission electric propulsion is an electrostatic space electric propulsion technology that offers various advantageous features including efficient design, high specific impulse, and versatile thrust capabilities ranging from micro-Newton to milli-Newton levels. These characteristics make FEEP a promising technology for small satellite platforms, enabling precise attitude control, orbit maintenance, and de-orbiting through ionization and acceleration of a liquid metal propellant. The growing demand for small propulsion systems in CubeSat platforms has spurred significant progress in modeling and characterizing FEEP thrusters with the aim to enhance their overall performance. However, little study has been conducted to investigate the effect of geometric configurations on electric fields or expelled ion trajectories for design optimization. In this study, multi-objective design optimization is performed by incorporating electrostatic simulation coupled with an analytical performance model into evolutionary algorithms based on prediction from surrogate modeling, aiming to optimize the thruster emission design to maximize thruster performance. Physical insights into the key design factors influencing the performance of FEEP have been gained by probing into the interaction between ion particles and electric field behavior within the thruster. It has been found that the length of the emitter tip has a significant effect on plume divergence, \textit{i.e.,} a longer emitter tip under the influence of electric field at higher emitter current tends to result in lower initial acceleration of emitted ions and subsequently wider spread or divergence of the ion beam. A shorter emitter tip, on the other hand, generates a sharper E-field gradient, resulting in a more focused and narrower ion beam. Additionally, sensitivity analysis has identified the mass flow rate and potential distributions as the most influential design factors on performance due to the active roles they
The global drive towards carbon neutrality has led to a significant increase in the number of power plants based on renewable energy sources (RES). Concurrently, numerous households are adopting RES to generate their ...
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The use of robotics in manufacturing is rapidly growing. One promising application in particular is the use of robots as machining platforms. Robotic machining offers many advantages such as large operating envelopes,...
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The use of robotics in manufacturing is rapidly growing. One promising application in particular is the use of robots as machining platforms. Robotic machining offers many advantages such as large operating envelopes, flexibility in operations and low installation and running costs. Robotic machining platforms much like computer numerically controlled (CNC) machine tools are commanded by numerical controllers (NCs) using the well established G-code part programming language (ISO-6983). Toolpaths are defined in the work piece coordinate system (WCS) as a series of discrete tool centre point (TCP) positions and tool orientations. The role of the NC is to generate smooth feed drive or robot joint commands such that the tool or end effector travels along the commanded toolpath whilst satisfying TCP position and orientation tolerances and robot/machine tool kinematic constraints. Interpolating tool orientations directly in the WCS requires complex real-time spherical interpolation computations. Overcoming this challenge, this paper introduces a C 4 continuous tool path trajectory generation method for 6DOF motion. The tool centre point position is smoothed in the WCS, however, the tool orientation is smoothed directly in the rotary coordinate system without the requirement for spherical interpolation. The interpolated tool orientation trajectory follows the path of the great circle arc using the modified Haversine method eliminating non-linear interpolation errors present in linear interpolation of rotary axis positions (machine coordinate system interpolation). The proposed method is validated by simulation of a 6DOF robotic manipulator.
Continuum manipulator modeling is always associated with structured and unstructured uncertainties. Therefore, model-based control system design for this class of robotic systems will be very challenging. On the other...
Continuum manipulator modeling is always associated with structured and unstructured uncertainties. Therefore, model-based control system design for this class of robotic systems will be very challenging. On the other hand, the performance quality of model-free controllers is completely dependent on their hyperparameters; they are also very sensitive to the considered trajectory for the system. As a result, using model-free controllers will require setting parameters for different scenarios. In this research, the design of a model-free controller with comparable performance to model-based control strategies is presented. To this end, various parameters are determined online by the gain adjustment system. The research innovation is to use a supervised machine learning method, fuzzy inference system (FIS), to implement the intelligent gain adaptation system to achieve this goal. The Modified Transpose Jacobian (MTJ) performs well in trajectory tracking due to its approximated feedback linearization tool. In addition, the PID controller structure makes it a locally robust control strategy. An adaptive gain adjustment system can greatly increase algorithm potential and establish the capability to follow trajectories in different work points in the system work space. This research aims to improve the performance of the MTJ model-free control strategy in tracking trajectories starting from arbitrary initial conditions in the system work space. This is achieved by the gain adjustment system design using a fuzzy inference system. Both simulation and experimental results reveal the merits of the proposed controller.
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