机器人系统有限时间自适应迭代学习控制

研究任意初态下，机器人系统的有限时间自适应迭代学习控制方法。引入初始修正吸引子的概念，构造一个含有初始修正项的误差变量。针对定常机器人系统和时变机器人系统，采用Lyapunov-like方法，分别设计迭代学习控制器处理系统中不确定性。并且，采用未含/含限幅学习机制，保证闭环系统各变量的一致有界性和误差变量在整个作业区间一致收敛性。藉以实现跟踪误差在预先指定区间的完全跟踪。仿真结果验证所设计控制方法的有效性。     

Plant inspection by using a ground vehicle and an aerial robot: lessons learned from plant disaster prevention challenge in world robot summit 2018

Abstract

In recent years, to prevent accidents and disaster are desired by implementing maintenance and management of facilities, such as conducting periodic inspections with appropriate frequency at plants. However, because the dangerous materials such as flammable gas and explosives is used in a plant, and there are many dangerous places in a plant such as high-temperature environment and high places and narrow spaces, it is desirable to use a remote-controlled robot for safety work and short inspections. Against this background, the Disaster Robotics Category-Plant Disaster Prevention Challenge was held in Japan at the World Robot Summit 2018. Our team was ranked 3rd in this competition, because our strategy of ‘inspection and investigation in cooperation with UGV and UAV’ was effective. In this paper, the competition contents of World Robot Summit 2018 and the robot inspection system that we are studying are explained. And what kind of strategy was challenged and result for these given competition tasks by using our robot system are introduced. And the lessons learned such as advantages and issues in UGV and UAV collaboration work at this competition are described for evaluate a robot investigation system for disaster response and inspection work at plants.     

Modeling,tracking, vibration and balance control of an underactuated mobile manipulator (UMM)

This paper presents an underactuated mobile manipulator (UMM) and focuses on solving modeling, tracking, and vibration- and balance-control problems. Although the study has been directed at warehousing applications, the developed techniques are general and can be applied to other applications. The derivation of equations of motion of the UMM, disturbance analysis, and model validation are investigated to reveal the actual system dynamics. Additionally, a simple but effective strategy is also developed to solve the equilibrium point and balance problem. Based on the dynamic model, two control architectures are proposed: Model Predictive Control (MPC) and MPC+Proportional-Integral (PI) with integral actions, respectively, and they can also be applied to other robotic systems. Compared to other MPC-based control strategies, the proposed controllers require less effort to implement in practice. Finally, simulations, experiments, and robustness verification are conducted and discussed, and the results are satisfactory.     

Comparison of joint angle,velocity and acceleration estimators for hydraulically actuated manipulators to a novel dynamical approach

Excavators are used for a wide range of applications like earthworks and material handling. Assistance systems are becoming more common to support the operator. For monitoring and control based assistance functions the angular position, velocity and acceleration of the joints from the working implement are required. Commercial systems often use inertial measurement units, consisting of triaxial accelerometers and gyroscopes, to accomplish an estimation of those states. A novel joint angle, velocity and acceleration estimation for hydraulic manipulators is proposed and compared to state of the art methods. A decentralized kinematic filter using no information about the underlying system and a centralized kinematic filter taking the system kinematics into account are implemented as state of the art approaches. Both filters only use inertial measurement units to obtain information about the current state of the system. The novel centralized dynamic filter uses the same information as the centralized kinematic filter and extends it by a dynamic model containing additional information about the angular acceleration due to pressure readings of the hydraulic cylinders. Kalman filtering is used to combine the derived system and measurement models with the sensor information. The methods are evaluated on a material handling excavator for single and coupled movements of the working implement. The novel centralized dynamic filter enables improvements for the angular acceleration estimation compared to the decentralized and centralized kinematic filter. Less noise of the acceleration estimation and a better tracking of the actual acceleration are shown.     

Participatory design of a robot for demonstrating an epileptic seizure

ABSTRACT

We present the methodology and results of participatory design of a robot for presenting an epileptic seizure and a scenario of the educational workshop using this robot. Children with epilepsy encounter stigma and stereotypes and may receive inadequate aid when having an epileptic seizure. The goal of the larger project was to use the prototype device in a series of workshops for improving teachers' actions during an epileptic seizure and their attitudes towards epileptic students. In this paper, we show how various design goals for an educational robot were accomplished to fit the needs of all identified stakeholders, particularly people with epilepsy.

We used a co-design (participatory design) approach through a series of meetings participated by members of the association Polish Association for People Suffering from Epilepsy, students and faculty members of the biomedical engineering and robotics departments, teachers, psychologists and medical specialists (epileptologist, neurologist).

These meetings created an opportunity for a better understanding of the (functional and nonfunctional) requirements and resulting tradeoffs and led the participants to find appropriate solutions. Participation of people with epilepsy in the design process allowed them to deal with the potentially stereotyped representation of themselves. The prototype robot, therefore, combined goals of various stakeholders, such as an accurate presentation of an epileptic seizure, lightweight, ease of use and control, while preserving the dignity of people with epilepsy.

As a result of the co-designing process, an inexpensive robot was created and used in a series of 10 pilot workshops with 217 participants, mainly teachers of primary and middle schools. Teachers improved their understanding of epilepsy and suggested further improvements to the system.     

轻量级电驱水下机械臂设计与运动学分析

设计了一款四功能水下机械臂，并对驱动关节进行了模块化设计和密封测试。为了保证水下机械臂的可靠性，在水下机械臂水下测试前，进行了强度校核和模态分析。为了验证水下机械臂的性能，通过 Ｄ- Ｈ法建立了其运动学模型，在此基础上分别进行了正、逆运动学分析。此外还采用蒙特卡洛法，在正运动学分析的基础上研究了工作空间特点。研究结果将为进一步的运动控制提供有益的帮助。     

Adaptive actuator failure compensation for cooperative robotic manipulators with parameter uncertainties

This article develops a new framework of adaptive actuator failure compensation control for cooperative manipulator systems with parameter uncertainties in addition to actuator failures, and designs and analyzes effective actuator failure compensation schemes for such robotic systems. The new adaptive control design uses an integration of multiple individual failure compensators and direct adaptation to handle various types of uncertainties in such robotic systems. The design can also be used for concurrent actuator failure cases, to expand the capability of adaptive actuator failure compensation. With a complete proof and performance analysis, it is shown that the proposed control scheme guarantees the desired closed-loop stability and asymptotic output tracking, despite actuator failures whose patterns, time instants and values are all unknown. Simulation results of a benchmark cooperative manipulator system are presented to verify the desired control performance of the system with both typical constant and square-wave actuator failure signals.     

Adaptive constraint control for flexible manipulator systems modeled by partial differential equations with dead-zone input

In this article, based on partial differential equations (PDEs), the flexible manipulator system with both dead-zone input and state constraints is studied. The dynamic model of the flexible manipulator system is described by PDEs. The parameters of the dead-zone input are unknown, and the state constraint problem is also considered. An adaptive approach is proposed to offset the effects caused by dead-zone input. Thus, to guarantee that all states remain within their respective constraint regions, the boundary control law based on the barrier Lyapunov function is given, and an adaptive controller is designed. According to the Lyapunov analysis method, the control method is given to ensure that all signals of the closed-loop system are bounded and all states satisfy the constraint conditions. Finally, simulation results show the effectiveness of the proposed control method in this article.     

Optimal design of nonlinear model predictive controller based on new modified multitracker optimization algorithm

The controller design for the robotic manipulator faces different challenges such as the system's nonlinearities and the uncertainties of the parameters. Furthermore, the tracking of different linear and nonlinear trajectories represents a vital role by the manipulator. This paper suggests an optimal design for the nonlinear model predictive control (NLMPC) based on a new improved intelligent technique and it is named modified multitracker optimization algorithm (MMTOA). The proposed modification of the MTOA is carried out based on opposition-based learning (OBL) and quasi OBL approaches. This modification improves the exploration behavior of the MTOA to prevent it from becoming trapped in a local optimum. The proposed method is applied on the robotic manipulator to track different linear and nonlinear trajectories. The NLMPC parameters are tuned by the MMTOA rather than the trial and error method of the designer. The proposed NLMPC based on MMTOA is compared with the original MTOA, genetic algorithm, and cuckoo search algorithm in literature. The superiority and effectiveness of the proposed controller are confirmed to track different linear and nonlinear trajectories. Furthermore, the robustness of the proposed method is emphasized against the uncertainties of the parameters.     

Design and analysis of a class of redundant collaborative manipulators with 2D large rotational angles

The parallel spindle heads with high rotational capability are demanded in the area of multi-axis machine tools and 3D printers. This paper focuses on designing a class of 2R1T (R: Rotation; T: Translation) parallel spindle heads and the corresponding collaborative 5-axis manipulators with 2-dimension (2D) large rotational angles. In order to construct 2D rotational degrees of freedom (DOFs), a platform with 2D revolute joints is proposed first. Based on the constraint screw theory, the feasible limbs that can be connected in the platform are synthesized. In order to provide constant rotational axis for the platform, a class of redundant limbs are designed. A class of redundant 2R1T parallel spindle heads is obtained by connecting the redundant limbs with the platform and the redundant characteristics are verified by the modified Grübler-Kutzbach criterion. The corresponding 5-axis collaborative manipulators are presented by constructing a 2-DOF series translational bottom moving platform. The inverse kinematics and the orientation workspace as well as the decoupling characteristics of this type of 2R1T parallel spindle heads are analyzed. The results show that these manipulators have large 2D rotational angles than the traditional A3/Z3 heads and can be potentially used in the application of multi-axis machine tools and the 3D printers.