关键词： Flexible robots   Flexible robotic arms   Kinematics   Dynamics   Finite elements method  

摘要： If two adjacent links of a flexible robot are connected via a revolute joint or a fixed prismatic joint, the relative motion of the next link will depend on both the joint motion and the elastic displacement of the distal end of the previous link. However, if the two adjacent links are connected via a sliding prismatic joint, the relative motion of the next link will depend additionally on the elastic deformation distributed along the previous link. Therefore, formulation of the motion equations for a multi-link flexible robot consisting of the revolute joints, the fixed prismatic joints and the sliding prismatic joints is challenging. In this study, the finite element kinematic and dynamic formulation was successfully developed and validated for the flexible robot, in which a transformation matrix is proposed to describe the kinematics of both the joint motion and the link deformation. Additionally, a new recursive formulation of the dynamic equations is introduced. As compared with the previous methods, the time complexity of the formulation is reduced by O(2 eta), where eta is the number of finite elements on all links. The numerical examples and experiments were implemented to validate the proposed kinematic and dynamic modelling method. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Computation offloading   QoS   robot swarms   cloud robotics   game theory  

摘要： Computation offloading is a promising solution to extend the capacity of robot swarms for computation-intensive applications because it allows robot swarms to benefit from the powerful computing resources of modern data centers. However, the existing computation-offloading approaches still face challenges: 1) multi-hop cooperative computation offloading, 2) joint computation offloading and routing, and 3) task slicing. In this paper, we propose a quality of service (QoS)-aware cooperative computation-offloading scheme for robot swarms using game theory. We analyze the multi-hop cooperative communication model in robot swarms and investigate the computation offloading and routing decision-making problems with the goals of both latency minimization and energy efficiency. We formulate the joint optimization problem as a multi-hop cooperative computation-offloading game and show the existence of a Nash equilibrium (NE) of the game for both unsliceable and sliceable tasks. We further propose a QoS-aware distributed algorithm to attain an NE and provide an upper bound on the price of anarchy in the game. Finally, our simulated results show that our algorithm scales well as the swarm size increases and it has a stable performance gain in various parameter settings.

关键词： Finite-time stability   output feedback stabilization   robotic systems  

摘要： The continuous finite-time stabilization of a broad class of lower-triangular nonlinear systems using output feedback is studied in this paper. The nonlinearities are only assumed to be Holder continuous. A constructive, continuous, finite-time, output-feedback stabilizer design is proposed based on a finite-time observer. Rigorous finite-time stability analysis is carried out for the closed-loop observer-controller system. The proposed design method is applied to a single-link robotic manipulator coupled to a dc motor.

摘要： The article offers information on the role of the robotics and navigation in orthopaedics. Topics discussed include the goal of machine-assisted surgery regarding preventing errors and improving accuracy and precision; research on machine-assistance for orthopaedic tumor resection and reconstruction, orthopaedic trauma and spine instrumentation; and considering machine-assistance as a training tool.

关键词： Computationally efficient inverse dynamics   Dual quaternion   6-UPS   6-PUS  

摘要： Computationally efficient inverse dynamics is crucial to the real-time application of parallel robots. This paper provides a computationally more efficient solution to the inverse dynamics of a class of six-DOF parallel robots based on the dual quaternion approach under the principle of virtual power. A unit dual quaternion is selected as the generalized coordinates of the system. The equations of motion are then constructed by the principle of virtual power. The dual quaternion constraints are eliminated by the null space formulation to obtain the inverse dynamic solution. It is revealed that in the new solution, the Jacobian matrices and the orthogonal complement matrix are all linear with respect to the generalized coordinates. Additionally, the positions, velocities and accelerations of all bodies are quadratic with respect to the generalized coordinates, velocities and accelerations. Such succinct expressions render the new solution computationally more efficient. The execution time of the dual quaternion approach and the traditional one are compared under the same condition by two different six-DOF parallel robots: 6-UPS and 6-PUS. The results show that the new solution can save the computational cost by 43.45% and 38.45% respectively for the two robots, illustrating the effectiveness of the proposed approach.

关键词： Mechanical engineering   Software  

摘要： Biological organisms achieve robust high-level behaviours by combining and coordinating stochastic low-level components(1-3). By contrast, most current robotic systems comprise either monolithic mechanisms(4,5) or modular units with coordinated motions(6,7). Such robots require explicit control of individual components to perform specific functions, and the failure of one component typically renders the entire robot inoperable. Here we demonstrate a robotic system whose overall behaviour can be successfully controlled by exploiting statistical mechanics phenomena. We achieve this by incorporating many loosely coupled 'particles', which are incapable of independent locomotion and do not possess individual identity or addressable position. In the proposed system, each particle is permitted to perform only uniform volumetric oscillations that are phase-modulated by a global signal. Despite the stochastic motion of the robot and lack of direct control of its individual components, we demonstrate physical robots composed of up to two dozen particles and simulated robots with up to 100,000 particles capable of robust locomotion, object transport and phototaxis (movement towards a light stimulus). Locomotion is maintained even when 20 per cent of the particles malfunction. These findings indicate that stochastic systems may offer an alternative approach to more complex and exacting robots via large-scale robust amorphous robotic systems that exhibit deterministic behaviour.

关键词： Swarm robotics   Multi-target search   Swarm intelligence optimization   Deep learning   Evolutionary algorithm   Strategy imitation  

摘要： As a distributed system with a large number of individuals, swarm robotics is particularly suitable for multi-target search problems. Most existing work is about strategic design while this article focuses on strategy imitation. Sometimes we can observe the behavior of individuals and obtain a large amount of data, but we do not know the specific details of the strategy behind the behavior. Imitating the self-organizing behavior of organisms is of great significance for us to design efficient swarm strategies and to reveal the underlying mechanisms. The actual strategy adopted by individuals can be called the target strategy, and in this article, a two-stage imitation learning framework is proposed to approach the target strategy. In the first stage, a deep neural network is trained using the behavioral data of individuals, and in the second stage, the parameters of the neural network are further fine-tuned using the evolutionary algorithm. After two stages of learning and evolution, the resulting strategy RNSE is very close to the target strategy in terms of multiple indicators, including search efficiency, stability, parallel processing capability, and collaborative processing capability. In addition to multi-target search, the framework can also be used for other collective tasks such as aggregation and dispersion. In this paper, the design of neural networks and the settings of the evolutionary algorithm are discussed in detail, which is of great significance for the migration application of the framework. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Co-simulation   kinematics   multi-software platform   rigid-flexible coupling dynamics   3-revolute-prismatic-sphericalparallel robot  

摘要： Kinematics and dynamics are the most important and basic tool for robot research. With the help of computer technology and the respective advantages of three kinds of software, a new method of co-simulation of parallel robot based on multi-platform is proposed, and the mechanical model of multi-body system of 3-revolute-prismatic-spherical parallel robot is established. According to the mechanical analysis of the parallel robot, the rigid-flexible coupling analysis method is adopted. The displacement error shows a periodic change with a period of 4.2 s and the maximum error is 2x10-4m. The dangerous part of the structure is the root of the lower link, and its maximum stress is 202.64 MPa less than the yield strength of the material. The multi-software platform co-simulation improves the accuracy of the dynamic response analysis of the part under dynamic load, and provides an important theoretical basis for the design and optimization of the parallel robot.

关键词： graphene   wrinkle and crumple structures   strain-insensitive electrodes   stretchable pressure sensors   surgical robotics  

摘要： Stretchable skin-like pressure sensing with minimized and distinguishable strain-induced interference is essential for the development of collision-aware surgical robotics to improve the safety and efficiency of minimally invasive surgery in a confined space. Inspired by the multidimensional wrinkles of Shar-Pei dog's skin for tactile sensing, we developed a stretchable pressure sensor consisting of reduced graphene oxide (rGO) electrodes with biomimetic topographies to improve the robot-tissue collision detections. A facile fabrication route for stretchable rGO electrodes was first demonstrated by harnessing the surface instability during the sequential deformation processes. The wrinkle-crumple rGO electrodes exhibited high stretchability (similar to 100%) and strain-insensitive resistance profiles [a gauge factor (GF) < 0.05], which were next utilized to fabricate piezoresistive pressure sensors. The rGO pressure sensors were highly stretchable and exhibited high sensitivity under uniaxial strains (1.37, 1.30, and 0.98 kPa(-1) at 0, 30, and 50% stretching states, respectively) along with distinguishable and reduced stretching responsiveness (a small GF similar to 0.2 under 40% strains). The stretchable pressure sensors were next integrated with two surgical robots for the transoral robotic surgery procedure. During the cadaveric testing, the rGO sensors can detect the robot-tissue contacts under joint stretches in real time to enhance the surgeon's awareness for collision avoidance. The stretchable rGO pressure sensor that is highly sensitive under large strains provides great potential in the fields of wearable sensing and collision aware humanoid robots to improve the human-machine interactions.

关键词： differentiable physics engine   deep learning   gradient descent   neural network controller   robotics  

摘要： An important field in robotics is the optimization of controllers. Currently, robots are often treated as a black box in this optimization process, which is the reason why derivative-free optimization methods such as evolutionary algorithms or reinforcement learning are omnipresent. When gradient-based methods are used, models are kept small or rely on finite difference approximations for the Jacobian. This method quickly grows expensive with increasing numbers of parameters, such as found in deep learning. We propose the implementation of a modern physics engine, which can differentiate control parameters. This engine is implemented for both CPU and GPU. Firstly, this paper shows how such an engine speeds up the optimization process, even for small problems. Furthermore, it explains why this is an alternative approach to deep Q-learning, for using deep learning in robotics. Finally, we argue that this is a big step for deep learning in robotics, as it opens up new possibilities to optimize robots, both in hardware and software.