Exoskeletal master device for dual arm robot teaching

Dual arm robots are used as humanoid or industrial robots for assembly work. Each arm of these robots is generally composed of 7-DOF to mimic the human arm. For motion teaching of this 7-DOF robot arm, upper limb exoskeletal master devices can be used, and each arm of the upper limb exoskeletal master device can also be composed of 7-DOF. However, the motions of the human shoulder are complex and the lack of DOF in the exoskeletal master device limits the wearer's motions and makes the wearer feel uncomfortable. We propose a compact-sized exoskeletal master device, each of whose arms are composed of two serially connected parts. One is a 6-DOF shoulder–elbow mechanism and the other is a 3-DOF wrist mechanism. The 6-DOF mechanism serially connects the base frame near the shoulder to a point on the forearm, and the center of rotation of the shoulder joint is shifted to the outside of the human shoulder. In addition, the 6-DOF mechanism includes a long stroke but short reduced-length prismatic joint. This 6-DOF mechanism enables unconstrained and comfortable shoulder motions. The 3-DOF wrist mechanism corresponds to forearm pronation/supination, wrist flexion/extension, and wrist adduction/abduction. The closed-loop inverse kinematic scheme is applied for the dual arm robot control in the task space. The performance of the exoskeletal master devices and control strategies are verified through experiments using a 14-DOF dual arm slave robot.     

Six-DOF Impedance Control of Dual-Arm Cooperative Manipulators

In this paper, the problem of impedance control of dual-arm cooperative manipulators is studied. A general impedance control scheme is adopted, which encompasses a centralized impedance control strategy, aimed at conferring a compliant behavior at the object level, and a decentralized impedance control, enforced at the end-effector level, aimed at avoiding large internal loading of the object. Remarkably, the mechanical impedance behavior is defined in terms of geometrically consistent stiffness. The overall control scheme is based on a two-loop arrangement, where a simple proportional integral derivative inner motion loop is adopted for each manipulator, while an outer loop, using force and moment measurements at the robots wrists, is aimed at imposing the desired impedance behaviors. The developed control scheme is experimentally tested on a dual-arm setup composed of two 6-DOF industrial manipulators carrying a common object. The experimental investigation concerns the four different controller configurations that can be achieved by activating/deactivating the single impedance controllers.     

Modeling and control of a humanoid robot

This work deals with modeling of humanoid robots, especially for planning motion using the Denavit-Hartenberg method to determine the inverse kinematics of used trajectory (Matlab/Simulink and SimMechanics). The simulations are applied to an existing robot, in order to determine the optimal trajectory for the robot motion.     

Parameter identification and vibration control in Modular manipulators

The joint parameters of modular manipulators are prerequisite data for effective dynamic control. A method for identifying these parameters using fuzzy logic was devised to study modular redundant robots. Experimental modal analysis and finite element modeling were exploited to model the dynamics. The joint parameters of a nine degrees-of-freedom (9-DOF) modular robot have been identified. In addition, active vibration control based on a neural network and a genetic algorithm were investigated. Ideal control simulation results for a reduced dynamic model of the 9-DOF modular robot were then derived.     

An Artificial Motion and Tactile Receptor Constructed by Hyperelastic Double Physically Cross-Linked Silk Fibroin Ionoelastomer

Ionotronic artificial motion and tactile receptor (i-AMTR) is essential to realize an interactive human-machine interface. However, an i-AMTR that effectively mimics the composition, structure, mechanics, and multi-functionality of human skin, called humanoid i-AMTR, is yet to be developed. To bridge this technological gap, this study proposes a strategy that combines molecular structure design and function integration to construct a humanoid i-AMTR. Herein, a silk fibroin ionoelastomer (SFIE) with double cross-linked molecular structure is designed to mimic the composition and structure of human skin, thereby resolving the conflict of stretchability, softness, and resilience, suffered by many previously reported ionotronics. Functionally, electromechanical sensing and triboelectricity-based tactile perception are integrated into SFIE, to enable simultaneous perception of both motion and tactile inputs. By further leveraging the machine learning and Internet of Things (IoT) techniques, the proposed SFIE-based humanoid i-AMTR precisely senses the movement of human body and accurately sortball objects made of different materials. Notably, the success rate for 610 sorting tests reaches as high as 92.3%. These promising results essentially demonstrate a massive potential of humanoid i-AMTR in the fields of sorting robots, rehabilitation medicine, and augmented reality.     

4-DOF多功能机器人运动控制算法的研究

随着机器人技术的不断发展,机器人在现在社会发展中发挥着越来越重要的作用。文中对实验室研发的多功能4-DOF机器人的运动控制相关问题进行研究。首先对4-DOF机器人的机构整体设计并PROE三维建模,然后通过基于D-H法建立机械臂坐标系,对4-DOF机器人进行运动学正逆解分析,在逆解计算中,提出了当两轴平行两轴耦合的计算方法,即将两轴关节角视为整体计算,再利用代数方法依次得出单个关节角。同时针对机械臂的连续轨迹运动给出轨迹规划的方法,为设计机械臂控制器的实现和机械臂的运动控制提供了依据。     

Automatic locomotion design and experiments for a Modular robotic system

This paper presents a design method and experiments for whole-body locomotion by a modular robot. There are two types of locomotion for modular robots: a repeating self-reconfiguration and whole-body motion such as walking or crawling. For whole-body locomotion, designing a control method is more difficult than for ordinary robots because a modular robotic system can form various configurations, each of which has many degrees of freedom. This study proposes a unified framework for automatically designing an efficient locomotion controller suitable for any module configuration. The method utilizes neural oscillators (central pattern generators, CPGs), each of which works as a distributed joint controller of each module, and a genetic algorithm to optimize the CPG network. We verified the method by software simulations and hardware experiments, in which our modular robotic system, named M-TRAN II, performed stable and effective locomotion in various configurations.     

Real-time state estimation for spatial six-degree-of-freedom linearly actuated parallel robots

This paper presents a novel numerical method, Global Newton–Raphson with Monotonic Descent algorithms (GNRMD), to solve the effectively real-time spatial 6-DOF states of parallel robots in practice. Based on geometrical frame of parallel robots, the highly nonlinear equations of system states estimation are obtained using analytical approach. GNRMD algorithms modified from Global Newton–Raphson method are developed to solve the nonlinear equations in real-time application. The procedure of GNRMD algorithms are programmed in MATLAB/Simulink, and then compiled to a real-time PC with Microsoft Visual Studio .NET for implementation. Applying the proposed algorithms, the real-time spatial 6-DOF states of the parallel robots are estimated. In addition, the performances, accuracy, convergence, property of real-time and effectiveness, of the proposed method are analyzed and verified in experiment and theory. Furthermore, the presented algorithms are used in a DOF control scheme of parallel robots. Simulation and experimental results show the proposed algorithms are effective and feasible for spatial states estimation of parallel robots, and are suitable for a real-time control system required accurate feedback of system states.     

Humanoid motion planning of robotic arm based on human arm action feature and reinforcement learning

The use and application of robotic arms in helping the aged and vulnerable persons are increasing gradually. In order to achieve safer and reliable human-robot interaction and its wider adoption, the requirements for the humanoid motion of robotic arms are becoming more stringent. This paper presents a humanoid motion planning method for a robotic arm based on the physics of human arm and reinforcement learning. Firstly, the humanoid motion rules are extracted by analyzing and learning the action data of human arm, which is collected using the VICON optical motion capture system. Then, according to the acquired features and rules, the corresponding reward functions are proposed and the humanoid motion training of the robotic arm is carried out by using the reinforcement learning based on Deep Deterministic Policy Gradient (DDPG) and Hindsight Experience Replay (HER) algorithm. Finally, the experiments are carried out to verify whether the robotic arm motions planned by the proposed approach are humanoid, and the observed results show its feasibility and effectiveness in planning the humanoid motion of the robotic arm.     

A compliant dual-axis gripper with integrated position and force sensing

This paper proposes a new flexure-based dual-axis gripper driven by two piezoelectric actuators (PEAs). For achieving two degree-of-freedom (2-DOF) micromanipulation in terms of grasping and rotating operation, the gripper is designed with an asymmetric structure which can be divided into left and right parts. Each part of the structure includes a two-stage amplification mechanism to accomplish displacement enlargement and motion transmission. Three groups of strain gages are integrated to measure the jaw displacements and the gripping force. To realize decoupling between the grasping and rotating function, the motion-guiding mechanisms of the two parts are elaborately designed with an orthogonal configuration. Analytical models of the gripper are derived using pseudo-rigid-body model (PRBM) method. Finite-element analysis (FEA) simulations are conducted to obtain the optimal geometric parameters and to evaluate the performance of the gripper. A close-loop position/force switching control strategy based on incremental PID algorithm is proposed to compensate the hysteretic nonlinearity of PEAs and guarantee precise and stable operation of the gripper. After that, a prototype gripper is developed and experimental investigations are conducted to verify the effectiveness of the gripper by executing a grasping-rotating-releasing operation of a metal wire. The experimental results indicate that the proposed gripper is capable of delicate and dexterous micromanipulation.     

A stable transition controller for constrained robots

This paper addresses the problem of contact transition from free motion to constrained motion for robots. Stability of transition from free motion to constrained motion is essential for successful operation of a robot performing general tasks such as surface following and surface finishing. Uncertainty in the location of the constraint can cause the robot to impact the constraint surface with a nonzero velocity, which may lead to bouncing of the robot end-effector on the surface. A new stable discontinuous transition controller is proposed to deal with contact transition problem. This discontinuous transition control algorithm is used when switching from free motion to constrained motion. Control algorithm for a complete robot task is developed. Extensive experiments with the proposed control strategy were conducted with different levels of constraint uncertainty and impact velocities. Experimental results show much improved transition performance and force regulation with the proposed controller. Details of the experimental platform and typical experimental results are given     

Real-Time Gait Planning for Pushing Motion of Humanoid Robot

This paper describes real-time gait planning for pushing motion of humanoid robots. This method deals with an object whose mass is not known. In order that a humanoid robot pushes an unknown object in both single support phase and double support phase, real-time gait planning for pushing the unknown object is proposed. Real-time gait planning consists of zero moment point (ZMP) modification and cycle time modification. ZMP modification is the method that modifies the influence of reaction force to ZMP. By cycle time modification, the period in double support phase is modified to avoid a robot tipping over. These modifications are calculated from reaction force on arms in every cycle. With these methods, trajectory planning for pushing an unknown object in both single support phase and double support phase is calculated. Even if parameters of an object and friction coefficient on the floor vary, the robot keeps on walking while pushing an object. The effectiveness of the proposed method is confirmed by a simulation and an experiment.     

Performance comparison of three planar 3-DOF parallel manipulators with 4-RRR, 3-RRR and 2-RRR structures

This paper presents a comparison study on the conditioning, velocity, payload and stiffness performance of three planar 3-DOF parallel manipulators with 4-RRR, 3-RRR and 2-RRR structures, respectively. The conditioning, velocity, payload and stiffness indices are developed to compare the performance of the three parallel manipulators. An optimum region is investigated. A comparison of the results indicates that the conditioning performance, payload performance and stiffness performance of the 4-RRR manipulator is the best, and those performances of the 2-RRR one is the worst. The three manipulators have different output velocity performance. The 4-RRR and 2-RRR manipulators have the largest and smallest optimum region, respectively.     

Optimum design of 2-DOF parallel manipulators with actuation redundancy

The optimum design of 2-DOF redundant parallel manipulators is investigated in this paper. The planar 2-DOF parallel manipulator with actuation redundancy is treated as non-dimensional structure. The physical model of the solution space is studied. Based on the kinematic model and Jacobian matrix, the global conditioning index, global velocity index and global stiffness index of the 2-DOF parallel manipulators are investigated, and the geometrical parameters without dimension are determined. Based on the optimum non-dimensional result, the optimum dimensional parameters are achieved. The result of this paper is useful for the development of 2-DOF 3-RRR redundant parallel manipulators.     

A Hybrid CPG–ZMP Controller for the Real-Time Balance of a Simulated Flexible Spine Humanoid Robot

Although a few researchers have started to realize the importance of a flexible spine in generating more natural-looking behaviors for humanoid robots, there has been no work on trying to make a full-body humanoid robot (that has a flexible spine) to maintain balance. The main reason for this is that it is very costly and difficult to develop and control this kind of robot. This paper serves two purposes. First, it proposes the use of a realistic 3-D robot simulator as a platform for costly flexible spine humanoid robotics research. Second, it presents a hybrid CPG-ZMP controller for the simulated robot. The biologically inspired CPG component of our controller allows the mechanical spine and feet to exhibit rhythmic motions using only two control parameters. Through monitoring the measured ZMP location, the engineering component modulates the neural activity of the CPG to allow the robot to maintain balance while it is standing and exhibiting motions on the sagittal and frontal planes in real time. The final postures of the simulated humanoid emerge automatically in real time through dynamic interactions between the neural networks, the robot itself, and its environment. Since experimental results have also demonstrated that our system is robust against disturbances from external pushing forces, our controller has the potential to be applicable to the next generation of humanoid robots.      

Control design of a novel compliant actuator for rehabilitation robots

Rehabilitation robots have direct physical interaction with human body. Ideally, actuators for rehabilitation robots should be compliant, force controllable, and back drivable due to safety and control considerations. Series Elastic Actuators (SEA) offers many advantages for these applications and various designs have been developed. However, current SEA designs face a common performance limitation due to the compromise on the spring stiffness selection. This paper presents a novel compact compliant force control actuator design for portable rehabilitation robots to overcome the performance limitations of current SEAs. Our design consists of a servomotor, a ball screw, a torsional spring between the motor and the ball screw, and a set of translational springs between the ball screw nut and the external load. The soft translational springs are used to handle the low force operation, while the torsional spring with high effective stiffness is used to deal with the large force operation. It is a challenging task to design the controller for such a novel design as the control system needs to handle both the force ranges. In this paper, we develop the force control strategy for this actuator. First, two dynamical models of the actuator are established based on different force ranges. Second, we propose an optimal control with friction compensation and disturbance rejection which is enhanced by a feedforward control for the low force range. The proposed optimal control with feedforward term is also extended to the high force range. Third, a switching control strategy is proposed to handle a transition between low force and high force control. The mathematical proof is given to ensure the stability of the closed-loop system under the proposed switching control. Finally, the proposed method is validated with experimental results on a prototype of the actuator system and is also verified with an ankle robot in walking experiments.     

小型仿人机器人的设计及步态规划

针对现有仿人形机器人造价高的缺点,设计一款低成本的小型双足机器人研究平台.根据人类步行过程及人体生理结构.依据模糊控制与专家控制相结合的理论提出一种简单的双足机器人模型.并根据仿生学原理确定机器人的自由度配置及各关节的比例尺寸.然后,利用目前通用的行为规划软件对双足机器人步态规划进行仿真.并在平坦地面上进行相应行走试验.实验证明.根据人行走模式对机器人进行步态规划的算法稳定可行.为机器人的教学和科研提供了良好的实验平台.     

Efficient rolling motion for snake-like robots utilizing center of gravity shift

Snake-like robots have attracted attention as robots that can travel over rough terrain where wheeled mobility mechanisms cannot. Previous research on snake-like robots has mainly focused on the biological movement of snakes; therefore, the issue of power consumption caused by driving a large number of actuators still remains unaddressed. In this study, we propose an efficient movement method using the movement of the center of gravity (COG) as a solution to the above-mentioned problem. In the proposed method, the snake-like robot is first transformed into a wheel shape, and then, some motors of the joint are moved to shift the COG and rotate the robot. Therefore, good movement efficiency can be achieved on leveled terrain by the rolling movement, and a snake-like undulating drive with high running performance can be selected on underwater and rough terrain. To realize the proposed movement method, we propose a method for switching between the rotational movement and undulation drive modes. However, the rolling motion with a COG shift needs a design of an appropriate orbit of the eccentric COG and timing of the motion stage transition. In this study, we demonstrate the rolling motion design with a simplified equation of motion. Next, experiments are conducted to verify the traveling efficiency in the proposed rolling mode, and it is proven that the method can achieve twice the traveling efficiency of the undulating motion.     

Development and evaluation of interactive humanoid robots

We report the development and evaluation of a new interactive humanoid robot that communicates with humans and is designed to participate in human society as a partner. A human-like body will provide an abundance of nonverbal information and enable us to smoothly communicate with the robot. To achieve this, we developed a humanoid robot that autonomously interacts with humans by speaking and gesturing. Interaction achieved through a large number of interactive behaviors, which are developed by using a visualizing tool for understanding the developed complex system. Each interactive behavior is designed by using knowledge obtained through cognitive experiments and implemented by using situated recognition. The robot is used as a testbed for studying embodied communication. Our strategy is to analyze human-robot interaction in terms of body movements using a motion-capturing system that allows us to measure the body movements in detail. We performed experiments to compare the body movements with subjective evaluation based on a psychological method. The results reveal the importance of well-coordinated behaviors as well as the performance of the developed interactive behaviors and suggest a new analytical approach to human-robot interaction.     

Analysis of effect of feedback current variation in CT Delta-Sigma modulators with Gm-C integrators

NAO humanoid robots are being used in many human-robot interaction applications. One of the important existing challenges is developing an accurate real-time face recognition system which does not require to have high computational cost. In this research work a real-time face recognition system by using block processing of local binary patterns of the face images captured by NAO humanoid is proposed. Majority voting and best score ensemble approaches have been used in order to boost the recognition results obtained in different colour channels of YUV colour space, which is a default colour space provided by the camera of NAO humanoid. The proposed method has been adopted on NAO humanoid and tested under real-world conditions. The recognition results were boosted in the real-time scenario by employing majority voting on the intra-sequence decisions with window size of 5. The experimental results are showing that the proposed face recognition algorithm overcomes the conventional and state-of-the-art techniques.