Soft robots based on particle jamming cannot return to the initial position and initial mechanical state due to the accumulation of particles after removing the particle jamming, which means poor restorability, and the compliance of the robots during deformation will be reduced because of the jamming effect. Here, we present the design, fabrication, and tests of a novel soft actuator with good restorability and compliance. To improve the restorability of the actuator, we used cotton threads to connect the spherical acrylic beads into form strings instead of discrete beads. The beads could be pulled to the initial position by the threads, the actuator also returns to the initial state. To avoid the jamming effect during the deformation of the actuator, we used compressed air to drive the actuator and injected the beads into the actuator after the active deformation. To reduce the driving pressure and facilitate the flow of the beads, an initial noncontact, frame-type strain constraint structure was designed for the soft actuator. Experimental data show that the actuator was flexible during bending and the stiffness can increase more than 12-fold to resist the external load. By pulling the threads, the actuator could be restored to the initial state with an error of less than 3% of the actuator length after an operation cycle. The soft gripper based on the actuator can grasp repeatedly or laterally. The gripper can grasp soft objects such as a piece of tofu and a balloon of water, and the maximum weight that can be stably grasped is 2.744 kg.

Virtual character has been widely adopted in many areas, such as virtual assistant, virtual customer service, robotics and etc. In this paper, we focus on its application in e-commerce live streaming. Particularly, we propose a virtual character generation and animation system that supports e-commerce live streaming with virtual characters as anchors. The system offers a virtual character face generation tool based on a weakly supervised 3D face reconstruction method. The method takes a single photo as input and generates a 3D face model with both similarity and aesthetics considered. It does not require 3D face annotation data due to the assist of differentiable neural rendering technique which seamlessly integrates rendering into a deep learning based 3D face reconstruction framework. Moreover, the system provides two animation approaches which support two different ways of live stream respectively. The first approach is based on real-time motion capture. An actor's performance is captured in real-time via a monocular camera, and then utilized for animating a virtual anchor. The second approach is text driven animation, in which the human-like animation is automatically generated based on a text script. The relationship between text script and animation is learned based on the training data which can be accumulated via the motion capture based animation. To our best knowledge, the presented work is the first sophisticated virtual character generation and animation system that is designed for e-commerce live streaming and actually deployed on an online shopping platform with millions of daily audiences.

In SDN, the controller is the core and is responsible for processing all flow requests of the network switches. However, due to the sudden occurrence and unbalanced distribution of flows in the network, it is likely that some controllers suffer workload that is far heavier than their load capacity, which leads to the failure of the controller and further leads to the paralysis of the entire network. To solve this problem, we propose a dynamic flow redirection scheme (DFR) to prevent network crash. We describe the phenomenon of controller failure caused by numerous flow requests. The flow redirection is formalized as a multi-objective optimization problem and constrained by flow table and bandwidth. We prove that the problem is NP-hard. We solve this problem with the dynamic flow redirection approach (DFR). First, state detection module detects whether the current flow requests will exceed the controller load. The Flow Redirection Assignment Module then computes the redirect path for the redundant flow request. Finally, Rule Dispense issues the flow rules to the corresponding switches. Simulation results show that DFR reduces network latency and reduces the overload probability of controllers by at least 3 times.

Abstract We present an approach to fabricate shell objects with thickness parameters, which are computed to maintain the user‐specified structural stability. Given a boundary surface and user‐specified external forces, we optimize the thickness parameters according to stress constraints to extrude the surface. Our approach mainly consists of two technical components: First, we develop a patch‐based shell simulation technique to efficiently support the static simulation of extruded shell objects using finite element methods. Second, we analytically compute the derivative of stress required in the sensitivity analysis technique to turn the optimization into a sequential linear programming problem. Experimental results demonstrate that our approach can optimize the thickness parameters for arbitrary surfaces in a few minutes and well predict the physical properties, such as the deformation and stress of the fabricated object.