Andrea Calanca

A Review of Algorithms for Compliant Control of Stiff and Fixed-Compliance Robots

This survey presents the state of the art of basic compliant control algorithms in a unified view of past and present literature. Compliant control is fundamental when dealing with unstructured environments, as in the case of human-robot interaction. This is because it implicitly controls the energy transfer to the environment, providing a safe interaction. In this review, we analyze solutions from traditional robotics, usually involving stiff joints, and recent literature to find common control concepts and differences. To this aim, we bring back every schemas and relative mathematics formulation to a common and simplified scenario. Then, for each schema, we explain its intuitive meaning and report issues raised in the literature. We also propose an expansion of taxonomy to account for recent research.

Human-adaptive control of series elastic actuators

Force-controlled series elastic actuators (SEAs) are the widely used components of novel physical human–robot interaction applications such as assistive and rehabilitation robotics. These systems are characterized by the presence of the “human in the loop” so that control response and stability depend on uncertain human dynamics. A common approach to guarantee stability is to use a passivity-based controller. Unfortunately, existing passivity-based controllers for SEAs do not define the performance of the force/torque loop. We propose a method to obtain predictable force/torque dynamics based on adaptive control and oversimplified human models. We propose a class of stable human-adaptive algorithms and experimentally show advantages of the proposed approach.

An Inverse Dynamics-Based Discrete-Time Sliding Mode Controller for Robot Manipulators

In the past years an extensive literature has been devoted to the subject of motion control of rigid robot manipulators. Many approaches have been proposed, such as feedback linearization [1], model predictive control [2], as well as sliding mode or adaptive control [3], [4], [5]. The basic idea of feedback linearization, known in the robotic context as inverse dynamics control [6], [7], is to exactly compensate all the coupling nonlinearities in the dynamical model of the manipulator in a first stage so that a second stage compensator may be designed based on a linear and decoupled plant. Although global feedback linearization is possible in theory, in practice it is difficult to achieve, mainly because the coordinate transformation is a function of the system parameters and, hence, sensitive to uncertainties which arise from joint and link flexibility, frictions, sensor noise, and unknown loads. This is the reason why the inverse dynamics approach is often coupled with robust control methodologies [1].

On the Role of Compliance in Force Control

This paper proposes an overview and an interpretation on the role of compliance in force control within a framework where adaptive control arise as an intuitive approach. In our analysis, we show that force control stability can be assured only if exists a compliant interface between the robot and the environment. Also, we prove that compliance is helpful to ensure well-defined force control dynamics, if combined with a low robot inertia. Otherwise adaptive control algorithms are proposed as a tool to deal with environment uncertainties. Finally, an experimental comparison between the adaptive approach and state of the art solutions is proposed.

Force control system for pneumatic actuators of an active gait orthosis

People affected by Cerebral Palsy suffer from physical disabilities that prevent the control over movement, making the walking difficult or even impossible. Treatment for these patients are orthosis to support their legs. While passive orthosis are nowadays quite common, active assistive orthosis are not preferred due to design limitations in the usage and their high cost. ARGO, the Active Reciprocated Gait Orthosis we developed, is a device that overcomes some of the limitations of the state of the art. It is realized from a passive commercial reciprocated gait orthosis, applying sensors and pneumatic artificial muscles to it. With ARGO we aim at reducing patients fatigue during orthosis usage, and at the same time, collect informations for a clinical validation of the treatment. To move limbs in a non coercive way, following users intention to move, ARGO deploys an innovative force-based control. It exploits both a neural network and a PID to obtain a fast and oscillations-free responses. In this article we introduce ARGO and present details and results of our high-performance control system.

Impedance control of series elastic actuators based on well-defined force dynamics

Abstract Modern rehabilitation and assistive robots are usually designed with impedance-controlled compliant actuators. Impedance control is usually implemented based on an inner force loop which assumed to be very fast. Unfortunately force control performance can be influenced by the human dynamics leading to inaccurate impedance rendering. In our previous work we solved this force control issue by proposing a human-adaptive force controller which guarantees predictable performance in spite of uncertainties in the human. In this paper we propose a robustified human-adaptive control law and ensuring asymptotic stability instead of globally uniformly ultimately boundedness. Then, we analyze the application of human-adaptive force control on impedance rendering. We show (i) that impedance accuracy is improved with respect to standard solutions and (ii) that, leveraging on human-adaptive control, impedance accuracy may not need high bandwidth inner force control. Simulation and experimental results validate the proposed method and compare it with a widely used impedance control algorithm.

A motor learning oriented, compliant and mobile Gait Orthosis

People affected by Cerebral Palsy suffer from physical disabilities due to irreversible neural impairment since the very beginning of their life. Difficulties in motor control and coordination often relegate these patients to the use of a wheelchair and to the unavoidable upcoming of disuse syndromes. As pointed out in recent literature Damiano [7] physical exercise, especially in young ages, can have a deep impact on the patient health and quality of life. For training purposes is very important to keep an upright position, although in some severe cases this is not trivial. Many commercial mobile orthoses are designed to facilitate the standing, but not all the patients are able to deploy them. ARGO, the Active Reciprocated Gait Orthosis we developed, is a device that overcomes some of the limitations of these devices. It is an active device that is realized starting from a commercial reciprocated Gait Orthosis applying sensors and actuators to it. With ARGO we aim to develop a device for helping limbs in a non-coercive way accordingly to users intention. In this way patients can drive the orthosis by themselves, deploying augmented biofeedback over movements. In fact Cerebral Palsy patients usually have weak biofeedback mechanisms and consequently are hardly inclined to learn movements. To achieve this behavior ARGO deploys a torque planning algorithm and a force control system. Data collected from a single case of study shows benefits of the orthosis. We will show that our test patient reaches complete autonomous walking after few hour of training with prototype.

A Parallel-Elastic Actuator for a Torque-Controlled Back-Support Exoskeleton

A torque-controlled back-support exoskeleton to assist manual handling is presented. Its objective is to provide a significant portion of the forces necessary to carry out the physical task, thereby reducing the compressive loads on the lumbar spine and the associated risk of injury. The design rationale for a parallel-elastic actuator (PEA) is proposed to match the asymmetrical torque requirements associated with the target task. The parallel spring relaxes the maximum motor torque requirements, with substantial effects on the resulting torque-control performance. A formal analysis and experimental evaluation is presented with the goal of documenting the improvement in performance. To this end, the proposed PEA is compared with a more traditional configuration without the parallel spring. The formal analysis and experimental results highlight the importance of the motor inertia reflected through the gearbox and illustrate the improvements in the proposed measures of torque-control performance.

A Rationale for Acceleration Feedback in Force Control of Series Elastic Actuators

Series elastic actuators (SEAs) have become fundamental components in robots that physically interact with unstructured environments and humans. Force control of SEAs is indeed an active area of research. This paper proposes a theoretical foundation for acceleration feedback (AF) in SEA force control. Even if AF already appeared in early works on SEAs, its advantages have not been properly highlighted in the literature. In particular, this paper formally motivates improved performance robustness and transparency exactly as if using a softer and lighter actuator. Taking advantage of AF, we propose a generic control architecture characterized by impressive performance robustness in spite of even high environment uncertainties. A comparison with state-of-the-art force control solutions such as disturbance observers and adaptive controllers is reported using a comprehensive set of simulations and experiments. As a result, AF methods exhibit the higher performance robustness and accuracy. Beside this outcome, AF controllers are extremely easy to implement and the rise of low-cost miniaturized accelerometers based on micro electro-mechanical systems (MEMS) represents an additional motivations for their use.

Impedance Control of Series Elastic Actuators Using Acceleration Feedback

More and more robots are designed to help or substitute humans both in daily activities and dangerous scenarios. These robots should be able to cope with humans and with other robots and to move in houses, factories, hospitals and uncertain outdoor terrains.