Robot Composite Learning and the Nunchaku Flipping Challenge

Advanced motor skills are essential for robots to physically coexist with humans. Much research on robot dynamics and control has achieved success on hyper robot motor capabilities, but mostly through heavily case-specific engineering. Meanwhile, in terms of robot acquiring skills in a ubiquitous manner, robot learning from human demonstration (LfD) has achieved great progress, but still has limitations handling dynamic skills and compound actions. In this paper, we present a composite learning scheme which goes beyond LfD and integrates robot learning from human definition, demonstration, and evaluation. The method tackles advanced motor skills that require dynamic time-critical maneuver, complex contact control, and handling partly soft partly rigid objects. We also introduce the "nunchaku flipping challenge", an extreme test that puts hard requirements to all these three aspects. Continued from our previous presentations, this paper introduces the latest update of the composite learning scheme and the physical success of the nunchaku flipping challenge

Passivity-Based adaptive bilateral teleoperation control for uncertain manipulators without jerk measurements

In this work, we consider the bilateral teleoperation problem of cooperative robotic systems in a Single-Master Multi-Slave (SM/MS) configuration, which is able to perform load transportation tasks in the presence of parametric uncertainty in the robot kinematic and dynamic models. The teleoperation architecture is based on the two-layer approach placed in a hierarchical structure, whose top and bottom layers are responsible for ensuring the transparency and stability properties respectively. The load transportation problem is tackled by using the formation control approach wherein the desired translational velocity and interaction force are provided to the master robot by the user, while the object is manipulated with a bounded constant force by the slave robots. Firstly, we develop an adaptive kinematic-based control scheme based on a composite adaptation law to solve the cooperative control problem for robots with uncertain kinematics. Secondly, the dynamic adaptive control for cooperative robots is implemented by means of a cascade control strategy, which does not require the measurement of the time derivative of force (which requires jerk measurements). The combination of the Lyapunov stability theory and the passivity formalism are used to establish the stability and convergence property of the closed-loop control system. Simulations and experimental results illustrate the performance and feasibility of the proposed control scheme.No presente trabalho, considera-se o problema de teleoperação bilateral de um sistema robótico cooperativo do tipo single-master e multiple-slaves (SM/MS) capaz de realizar tarefas de transporte de carga na presença de incertezas paramétricas no modelo cinemático e dinâmico dos robôs. A arquitetura de teleoperação está baseada na abordagem de duas camadas em estrutura hierárquica, onde as camadas superior e inferior são responsáveis por assegurar as propriedades de transparência e estabilidade respectivamente. O problema de transporte de carga é formulado usando a abordagem de controle de formação onde a velocidade de translação desejada e a força de interação são fornecidas ao robô mestre pelo operador, enquanto o objeto é manipulado pelos robôs escravos com uma força constante limitada. Primeiramente, desenvolve-se um esquema de controle adaptativo cinemático baseado em uma lei de adaptação composta para solucionar o problema de controle cooperativo de robôs com cinemática incerta. Em seguida, o controle adaptativo dinâmico de robôs cooperativos é implementado por meio de uma estratégia de controle em cascata, que não requer a medição da derivada da força (o qual requer a derivada da aceleração ou jerk). A teoria de estabilidade de Lyapunov e o formalismo de passividade são usados para estabelecer as propriedades de estabilidade e a convergência do sistema de controle em malha-fechada. Resultados de simulações numéricas ilustram o desempenho e viabilidade da estratégia de controle proposta

Modeling and Control of Flexible Link Manipulators

Autonomous maritime navigation and offshore operations have gained wide attention with the aim of reducing operational costs and increasing reliability and safety. Offshore operations, such as wind farm inspection, sea farm cleaning, and ship mooring, could be carried out autonomously or semi-autonomously by mounting one or more long-reach robots on the ship/vessel. In addition to offshore applications, long-reach manipulators can be used in many other engineering applications such as construction automation, aerospace industry, and space research. Some applications require the design of long and slender mechanical structures, which possess some degrees of flexibility and deflections because of the material used and the length of the links. The link elasticity causes deflection leading to problems in precise position control of the end-effector. So, it is necessary to compensate for the deflection of the long-reach arm to fully utilize the long-reach lightweight flexible manipulators. This thesis aims at presenting a unified understanding of modeling, control, and application of long-reach flexible manipulators. State-of-the-art dynamic modeling techniques and control schemes of the flexible link manipulators (FLMs) are discussed along with their merits, limitations, and challenges. The kinematics and dynamics of a planar multi-link flexible manipulator are presented. The effects of robot configuration and payload on the mode shapes and eigenfrequencies of the flexible links are discussed. A method to estimate and compensate for the static deflection of the multi-link flexible manipulators under gravity is proposed and experimentally validated. The redundant degree of freedom of the planar multi-link flexible manipulator is exploited to minimize vibrations. The application of a long-reach arm in autonomous mooring operation based on sensor fusion using camera and light detection and ranging (LiDAR) data is proposed.publishedVersio

Manipulation strategies for massive space payloads

Control for the bracing strategy is being examined. It was concluded earlier that trajectory planning must be improved to best achieve the bracing motion. Very interesting results were achieved which enable the inverse dynamics of flexible arms to be calculated for linearized motion in a more efficient manner than previously published. The desired motion of the end point beginning at t=0 and ending at t=t sub f is used to calculate the required torque at the joint. The solution is separated into a causal function that is zero for t is less than 0 and an accusal function which is zero for t is greater than t sub f. A number of alternative end point trajectories were explored in terms of the peak torque required, the amount of anticipatory action, and other issues. The single link case is the immediate subject and an experimental verification of that case is being performed. Modeling with experimental verification of closed chain dynamics continues. Modeling effort has pointed out inaccuracies that result from the choice of numerical techniques used to incorporate the closed chain constraints when modeling our experimental prototype RALF (Robotic Arm Large and Flexible). Results were compared to TREETOPS, a multi body code. The experimental verification work is suggesting new ways to make comparisons with systems having structural linearity and joint and geometric nonlinearity. The generation of inertial forces was studied with a small arm that will damp the large arm's vibration

Collaborative human-machine interfaces for mobile manipulators.

The use of mobile manipulators in service industries as both agents in physical Human Robot Interaction (pHRI) and for social interactions has been on the increase in recent times due to necessities like compensating for workforce shortages and enabling safer and more efficient operations amongst other reasons. Collaborative robots, or co-bots, are robots that are developed for use with human interaction through direct contact or close proximity in a shared space with the human users. The work presented in this dissertation focuses on the design, implementation and analysis of components for the next-generation collaborative human machine interfaces (CHMI) needed for mobile manipulator co-bots that can be used in various service industries. The particular components of these CHMI\u27s that are considered in this dissertation include: Robot Control: A Neuroadaptive Controller (NAC)-based admittance control strategy for pHRI applications with a co-bot. Robot state estimation: A novel methodology and placement strategy for using arrays of IMUs that can be embedded in robot skin for pose estimation in complex robot mechanisms. User perception of co-bot CHMI\u27s: Evaluation of human perceptions of usefulness and ease of use of a mobile manipulator co-bot in a nursing assistant application scenario. To facilitate advanced control for the Adaptive Robotic Nursing Assistant (ARNA) mobile manipulator co-bot that was designed and developed in our lab, we describe and evaluate an admittance control strategy that features a Neuroadaptive Controller (NAC). The NAC has been specifically formulated for pHRI applications such as patient walking. The controller continuously tunes weights of a neural network to cancel robot non-linearities, including drive train backlash, kinematic or dynamic coupling, variable patient pushing effort, or slope surfaces with unknown inclines. The advantage of our control strategy consists of Lyapunov stability guarantees during interaction, less need for parameter tuning and better performance across a variety of users and operating conditions. We conduct simulations and experiments with 10 users to confirm that the NAC outperforms a classic Proportional-Derivative (PD) joint controller in terms of resulting interaction jerk, user effort, and trajectory tracking error during patient walking. To tackle complex mechanisms of these next-gen robots wherein the use of encoder or other classic pose measuring device is not feasible, we present a study effects of design parameters on methods that use data from Inertial Measurement Units (IMU) in robot skins to provide robot state estimates. These parameters include number of sensors, their placement on the robot, as well as noise properties on the quality of robot pose estimation and its signal-to-noise Ratio (SNR). The results from that study facilitate the creation of robot skin, and in order to enable their use in complex robots, we propose a novel pose estimation method, the Generalized Common Mode Rejection (GCMR) algorithm, for estimation of joint angles in robot chains containing composite joints. The placement study and GCMR are demonstrated using both Gazebo simulation and experiments with a 3-DoF robotic arm containing 2 non-zero link lengths, 1 revolute joint and a 2-DoF composite joint. In addition to yielding insights on the predicted usage of co-bots, the design of control and sensing mechanisms in their CHMI benefits from evaluating the perception of the eventual users of these robots. With co-bots being only increasingly developed and used, there is a need for studies into these user perceptions using existing models that have been used in predicting usage of comparable technology. To this end, we use the Technology Acceptance Model (TAM) to evaluate the CHMI of the ARNA robot in a scenario via analysis of quantitative and questionnaire data collected during experiments with eventual uses. The results from the works conducted in this dissertation demonstrate insightful contributions to the realization of control and sensing systems that are part of CHMI\u27s for next generation co-bots

[Advanced Development for Space Robotics With Emphasis on Fault Tolerance Technology]

This report describes work developing fault tolerant redundant robotic architectures and adaptive control strategies for robotic manipulator systems which can dynamically accommodate drastic robot manipulator mechanism, sensor or control failures and maintain stable end-point trajectory control with minimum disturbance. Kinematic designs of redundant, modular, reconfigurable arms for fault tolerance were pursued at a fundamental level. The approach developed robotic testbeds to evaluate disturbance responses of fault tolerant concepts in robotic mechanisms and controllers. The development was implemented in various fault tolerant mechanism testbeds including duality in the joint servo motor modules, parallel and serial structural architectures, and dual arms. All have real-time adaptive controller technologies to react to mechanism or controller disturbances (failures) to perform real-time reconfiguration to continue the task operations. The developments fall into three main areas: hardware, software, and theoretical

2020 NASA Technology Taxonomy

This document is an update (new photos used) of the PDF version of the 2020 NASA Technology Taxonomy that will be available to download on the OCT Public Website. The updated 2020 NASA Technology Taxonomy, or "technology dictionary", uses a technology discipline based approach that realigns like-technologies independent of their application within the NASA mission portfolio. This tool is meant to serve as a common technology discipline-based communication tool across the agency and with its partners in other government agencies, academia, industry, and across the world