Admittance-based controller design for physical human-robot interaction in the constrained task space

In this article, an admittance-based controller for physical human-robot interaction (pHRI) is presented to perform the coordinated operation in the constrained task space. An admittance model and a soft saturation function are employed to generate a differentiable reference trajectory to ensure that the end-effector motion of the manipulator complies with the human operation and avoids collision with surroundings. Then, an adaptive neural network (NN) controller involving integral barrier Lyapunov function (IBLF) is designed to deal with tracking issues. Meanwhile, the controller can guarantee the end-effector of the manipulator limited in the constrained task space. A learning method based on the radial basis function NN (RBFNN) is involved in controller design to compensate for the dynamic uncertainties and improve tracking performance. The IBLF method is provided to prevent violations of the constrained task space. We prove that all states of the closed-loop system are semiglobally uniformly ultimately bounded (SGUUB) by utilizing the Lyapunov stability principles. At last, the effectiveness of the proposed algorithm is verified on a Baxter robot experiment platform. Note to Practitioners-This work is motivated by the neglect of safety in existing controller design in physical human-robot interaction (pHRI), which exists in industry and services, such as assembly and medical care. It is considerably required in the controller design for rigorously handling constraints. Therefore, in this article, we propose a novel admittance-based human-robot interaction controller. The developed controller has the following functionalities: 1) ensuring reference trajectory remaining in the constrained task space: A differentiable reference trajectory is shaped by the desired admittance model and a soft saturation function; 2) solving uncertainties of robotic dynamics: A learning approach based on radial basis function neural network (RBFNN) is involved in controller design; and 3) ensuring the end-effector of the manipulator remaining in the constrained task space: different from other barrier Lyapunov function (BLF), integral BLF (IBLF) is proposed to constrain system output directly rather than tracking error, which may be more convenient for controller designers. The controller can be potentially applied in many areas. First, it can be used in the rehabilitation robot to avoid injuring the patient by limiting the motion. Second, it can ensure the end-effector of the industrial manipulator in a prescribed task region. In some industrial tasks, dangerous or damageable tools are mounted on the end-effector, and it will hurt humans and bring damage to the robot when the end-effector is out of the prescribed task region. Third, it may bring a new idea to the designed controller for avoiding collisions in pHRI when collisions occur in the prescribed trajectory of end-effector

Design and implementation of haptic interactions

This thesis addresses current haptic display technology where the user interacts with a virtual environment by means of specialized interface devices. The user manipulates computer generated virtual objects and is able to feel the sense of touch through haptic feedback. The objective of this work is to design high performance haptic interactions by developing multi-purpose virtual tools and new control schemes to implement a PUMA 560 robotic manipulator as the haptic interface device. The interactions are modeled by coupling the motions of the virtual tool with those of the PUMA 560 robotic manipulator;The work presented in this dissertation uses both kinematic and dynamic based virtual manipulators as virtual simulators to address problems associated in both free and constrained motions. Both implementations are general enough to allow researchers with any six degree-of-freedom robot to apply the approaches and continue in this area of research. The results are expected to improve on the current haptic display technology by a new type of optimal position controller and better algorithms to handle both holonomic and nonholonomic constraints;Kane\u27s method is introduced to model dynamics of multibody systems. Multibody dynamics of a virtual simulator, a dumbbell, is developed and the advantages of the Kane\u27s method in handling the non-holonomic constraints are presented. The resulting model is used to develop an approach to dynamic simulation for use in interacting haptic display, including switching constraints. Experimental data is collected to show various contact configurations;A two-degree of freedom virtual manipulator is modeled to feel the surface of a taurus shape. An optimal position controller is designed to achieve kinematic coupling between the virtual manipulator and the haptic display device to impose motion constraints and the virtual interactions. Stability of the haptic interface is studied and proved using Lyapunov\u27s direct method. Experimental data in various positions of the robotic manipulator is obtained to justify theoretical results. A shift mechanism is then implemented on the taurus shape, thus the motions of the robotic manipulator is further constrained. The difficulties in handling the motion constraints are discussed and an alternative approach is presented

An aerial parallel manipulator with shared compliance

Accessing and interacting with difficult to reach surfaces at various orientations is of interest within a variety of industrial contexts. Thus far, the predominant robotic solution to such a problem has been to leverage the maneuverability of a fully actuated, omnidirectional aerial manipulator. Such an approach, however, requires a specialised system with a high relative degree of complexity, thus reducing platform endurance and real-world applicability. The work here presents a new aerial system composed of a parallel manipulator and conventional, underactuated multirotor flying base to demonstrate interaction with vertical and non-vertical surfaces. Our solution enables compliance to external disturbance on both subsystems, the manipulator and flying base, independently with a goal of improved overall system performance when interacting with surfaces. To achieve this behaviour, an admittance control strategy is implemented on various layers of the flying base's dynamics together with torque limits imposed on the manipulator actuators. Experimental evaluations show that the proposed system is compliant to external perturbations while allowing for differing interaction behaviours as compliance parameters of each subsystem are altered. Such capabilities enable an adjustable form of dexterity in completing sensor installation, inspection and aerial physical interaction tasks. A video of our system interacting with various surfaces can be found here: https://youtu.be/38neGb8-lXg

On the formulation of parallel position/force control schemes for industrial manipulators

In this paper, three commonly-used position/force control schemes namely Impedance, Admittance and Hybrid Position/Force control are investigated for use in industrial manipulators. In order to eliminate the instability problem that may occur in the customary versions of these schemes for large position errors, a modification is proposed, which is based on determining the joint-space position errors using inverse kinematic solutions rather than using the inverse Jacobian matrix. The feasibility of this modification relies on the fact that almost all of the industrial manipulators have easily obtainable inverse kinematic solutions. The simulation results showing the performance of the modified control schemes are also presented as applied on a Puma 560 manipulator

Predictive Context-Based Adaptive Compliance for Interaction Control of Robot Manipulators

In classical industrial robotics, robots are concealed within structured and well-known environments performing highly-repetitive tasks. In contrast, current robotic applications require more direct interaction with humans, cooperating with them to achieve a common task and entering home scenarios. Above all, robots are leaving the world of certainty to work in dynamically-changing and unstructured environments that might be partially or completely unknown to them. In such environments, controlling the interaction forces that appear when a robot contacts a certain environment (be the environment an object or a person) is of utmost importance. Common sense suggests the need to leave the stiff industrial robots and move towards compliant and adaptive robot manipulators that resemble the properties of their biological counterpart, the human arm. This thesis focuses on creating a higher level of intelligence for active compliance control methods applied to robot manipulators. This work thus proposes an architecture for compliance regulation named Predictive Context-Based Adaptive Compliance (PCAC) which is composed of three main components operating around a 'classical' impedance controller. Inspired by biological systems, the highest-level component is a Bayesian-based context predictor that allows the robot to pre-regulate the arm compliance based on predictions about the context the robot is placed in. The robot can use the information obtained while contacting the environment to update its context predictions and, in case it is necessary, to correct in real time for wrongly predicted contexts. Thus, the predictions are used both for anticipating actions to be taken 'before' proceeding with a task as well as for applying real-time corrective measures 'during' the execution of a in order to ensure a successful performance. Additionally, this thesis investigates a second component to identify the current environment among a set of known environments. This in turn allows the robot to select the proper compliance controller. The third component of the architecture presents the use of neuroevolutionary techniques for selecting the optimal parameters of the interaction controller once a certain environment has been identified

Admittance control of the intelligent assist robot manipulator for people with duchenne muscular dystrophy

Duchenne muscular dystrophy (DMD), a neuromuscular disease with a prevalence of 1 in 3500 male births, results in characteristic muscle weakness which is progressive with age and leads to loss of independence. And, in this population, maintaining optimal quality of life depends on the preservation of self-sufficiency. Despite the loss of function, non-ambulant people with DMD retain some muscle strength, just not sufficient strength to overcome the force of gravity. There are a number of upper-limb passive and active orthotic devices that attempt to augment the loss of upper limb function in people with DMD by taking advantage of this residual muscle strength by providing anti-gravity assistance. The majority of these devices, as well as currently available robotic manipulators, are considerably limited in the functionality that they provide, rendering them obtrusive and unaccommodating, resulting in lack of use by this population. This thesis presents the design of a novel upper limb assistive robotic device. This design involves the use of admittance control as the interface for the intelligent Assist Robot Manipulator (iARM). A thorough qualitative and quantitative analysis of the prototype is performed, the results of which are presented. The quantitative analysis focuses on the ideal delay that is required of human-machine interfaces to ensure comfort and passivity. Additionally, potential contributors to the delay of the iARM are investigated

Dyadic behavior in co-manipulation :from humans to robots

To both decrease the physical toll on a human worker, and increase a robot’s environment perception, a human-robot dyad may be used to co-manipulate a shared object. From the premise that humans are efficient working together, this work’s approach is to investigate human-human dyads co-manipulating an object. The co-manipulation is evaluated from motion capture data, surface electromyography (EMG) sensors, and custom contact sensors for qualitative performance analysis. A human-human dyadic co-manipulation experiment is designed in which every human is instructed to behave as a leader, as a follower or neither, acting as naturally as possible. The experiment data analysis revealed that humans modulate their arm mechanical impedance depending on their role during the co-manipulation. In order to emulate the human behavior during a co-manipulation task, an admittance controller with varying stiffness is presented. The desired stiffness is continuously varied based on a scalar and smooth function that assigns a degree of leadership to the robot. Furthermore, the controller is analyzed through simulations, its stability is analyzed by Lyapunov. The resulting object trajectories greatly resemble the patterns seen in the human-human dyad experiment.Para tanto diminuir o esforço físico de um humano, quanto aumentar a percepção de um ambiente por um robô, um díade humano-robô pode ser usado para co-manipulação de um objeto compartilhado. Partindo da premissa de que humanos são eficientes trabalhando juntos, a abordagem deste trabalho é a de investigar díades humano-humano co-manipulando um objeto compartilhado. A co-manipulação é avaliada a partir de dados de um sistema de captura de movimentos, sinais de eletromiografia (EMG), e de sensores de contato customizados para análise qualitativa de desempenho. Um experimento de co-manipulação com díades humano-humano foi projetado no qual cada humano é instruído a se comportar como um líder, um seguidor, ou simplesmente agir tão naturalmente quanto possível. A análise de dados do experimento revelou que os humanos modulam a rigidez mecânica do braço a depender de que tipo de comportamento eles foram designados antes da co-manipulação. Para emular o comportamento humano durante uma tarefa de co-manipulação, um controle por admitância com rigidez variável é apresentado neste trabalho. A rigidez desejada é continuamente variada com base em uma função escalar suave que define o grau de liderança do robô. Além disso, o controlador é analisado por meio de simulações, e sua estabilidade é analisada pela teoria de Lyapunov. As trajetórias resultantes do uso do controlador mostraram um padrão de comportamento muito parecido ao do experimento com díades humano-humano