Design and control of a novel variable stiffness soft arm

Soft robot arms possess such characteristics as light weight, simple structure and good adaptability to the environment, among others. On the other hand, robust control of soft robot arms presents many difficulties. Based on these reasons, this paper presents a novel design and modelling of a fuzzy active disturbance rejection control (FADRC) controller for a soft PAM arm. The soft arm comprises three contractile and one extensor PAMs, which can vary its stiffness independently of its position in space. Force analysis for the soft arm is conducted, and stiffness model of the arm is established based on the relational model of contractile and extensor PAM. The accuracy of stiffness model for the soft arm was verified through experiments. Associated to this, a controller based on the fuzzy adaptive theory and ADRC, FADRC, has been designed to control the arm. The fuzzy adaptive theory is used to adjust the parameters of the ADRC, the control algorithm has the ability to control stiffness and position of the soft arm. In this paper, FADRC was further verified through comparative experiments on the soft arm. This paper reinforces the hypothesis that FADRC control, as an algorithm, indeed possesses good robustness and adaptive abilities. Key words: soft robot, variable stiffness, PAM, stiffness modelling, FADR

The dimer state of GyrB is an active form: implications for the initial complex assembly and processive strand passage

In a previous study, we presented the dimer structure of DNA gyrase B′ domain (GyrB C-terminal domain) from Mycobacterium tuberculosis and proposed a ‘sluice-like’ model for T-segment transport. However, the role of the dimer structure is still not well understood. Cross-linking and analytical ultracentrifugation experiments showed that the dimer structure exists both in the B′ protein and in the full-length GyrB in solution. The cross-linked dimer of GyrB bound GyrA very weakly, but bound dsDNA with a much higher affinity than that of the monomer state. Using cross-linking and far-western analyses, the dimer state of GyrB was found to be involved in the ternary GyrA–GyrB–DNA complex. The results of mutational studies reveal that the dimer structure represents a state before DNA cleavage. Additionally, these results suggest that the dimer might also be present between the cleavage and reunion steps during processive transport

Reducing the Frame Vibration of Delta Robot in Pick and Place Application: An Acceleration Profile Optimization Approach

Delta robot is typically mounted on a frame and performs high speed pick and place tasks from top to bottom. Because of its outstanding accelerating capability and higher center of mass, the Delta robot can generate significant frame vibration. Existing trajectory smoothing methods mainly focus on vibration reduction for the robot instead of the frame, and modifying the frame structure increases the manufacturing cost. In this paper, an acceleration profile optimization approach is proposed to reduce the Delta robot-frame vibration. The profile is determined by the maximum jerk, acceleration, and velocity. The pick and place motion (PPM) and resulting frame vibration are analyzed in frequency domain. Quantitative analysis shows that frame vibration can be reduced by altering those dynamic motion parameters. Because the analytic model is derived based on several simplifications, it cannot be directly applied. A surrogate model-based optimization method is proposed to solve the practical issues. By directly executing the PPM with different parameters and measuring the vibration, a model is derived using Gaussian Process Regression (GPR). In order to reduce the frame vibration without sacrificing robot efficiency, those two goals are fused together according to their priorities. Based on the surrogate model, a single objective optimization problem is formulated and solved by Genetic Algorithm (GA). Experimental results show effectiveness of the proposed method. Behavior of the optimal parameters also verifies the robot-frame vibration mechanism

Virtual Constraints Based Control Design of an Inclined Translational Oscillator with Rotational Actuator System

Translational oscillator with rotational actuator (TORA) system, whose translational and rotational movements occur in horizontal planes, is a benchmark of underactuated mechanical systems for studying of control techniques. Currently, the research work of the benchmark mainly focuses on stabilizing control of equilibrium points of the dynamical system. The problem of steering TORA to arbitrary points in its state space is rarely studied. In this paper, the movements of the TORA system are extended to inclined planes and dynamics of the inclined TORA system is presented firstly. Following that, a trajectory tracking control method based on virtual constraints is proposed to steer the oscillations of the inclined TORA system. A virtual constraints based method is presented to generate periodic trajectories which pass through desired point; and a Lyapunov based control design is proposed to track the generated trajectories. Finally, the performance and feasibility of the proposed control design methodology are illustrated and analyzed according to numerical simulations

An Improved Point Cloud Descriptor for Vision Based Robotic Grasping System

In this paper, a novel global point cloud descriptor is proposed for reliable object recognition and pose estimation, which can be effectively applied to robot grasping operation. The viewpoint feature histogram (VFH) is widely used in three-dimensional (3D) object recognition and pose estimation in real scene obtained by depth sensor because of its recognition performance and computational efficiency. However, when the object has a mirrored structure, it is often difficult to distinguish the mirrored poses relative to the viewpoint using VFH. In order to solve this difficulty, this study presents an improved feature descriptor named orthogonal viewpoint feature histogram (OVFH), which contains two components: a surface shape component and an improved viewpoint direction component. The improved viewpoint component is calculated by the orthogonal vector of the viewpoint direction, which is obtained based on the reference frame estimated for the entire point cloud. The evaluation of OVFH using a publicly available data set indicates that it enhances the ability to distinguish between mirrored poses while ensuring object recognition performance. The proposed method uses OVFH to recognize and register objects in the database and obtains precise poses by using the iterative closest point (ICP) algorithm. The experimental results show that the proposed approach can be effectively applied to guide the robot to grasp objects with mirrored poses