Dance Teaching by a Robot: Combining Cognitive and Physical Human-Robot Interaction for Supporting the Skill Learning Process

This letter presents a physical human-robot interaction scenario in which a robot guides and performs the role of a teacher within a defined dance training framework. A combined cognitive and physical feedback of performance is proposed for assisting the skill learning process. Direct contact cooperation has been designed through an adaptive impedance-based controller that adjusts according to the partner's performance in the task. In measuring performance, a scoring system has been designed using the concept of progressive teaching (PT). The system adjusts the difficulty based on the user's number of practices and performance history. Using the proposed method and a baseline constant controller, comparative experiments have shown that the PT presents better performance in the initial stage of skill learning. An analysis of the subjects' perception of comfort, peace of mind, and robot performance have shown a significant difference at the p < .01 level, favoring the PT algorithm.Comment: Presented at IEEE International Conference on Robotics and Automation ICRA-201

Upper-limb Geometric MyoPassivity Map for Physical Human-Robot Interaction

The intrinsic biomechanical characteristic of the human upper limb plays a central role in absorbing the interactive energy during physical human-robot interaction (pHRI). We have recently shown that based on the concept of ``Excess of Passivity (EoP)," from nonlinear control theory, it is possible to decode such energetic behavior for both upper and lower limbs. The extracted knowledge can be used in the design of controllers for optimizing the transparency and fidelity of force fields in human-robot interaction and in haptic systems. In this paper, for the first time, we investigate the frequency behavior of the passivity map for the upper limb when the muscle co-activation was controlled in real-time through visual electromyographic feedback. Five healthy subjects (age: 27 +/- 5) were included in this study. The energetic behavior was evaluated at two stimulation frequencies at eight interaction directions over two controlled muscle co-activation levels. Electromyography (EMG) was captured using the Delsys Wireless Trigno system. Results showed a correlation between EMG and EoP, which was further altered by increasing the frequency. The proposed energetic behavior is named the Geometric MyoPassivity (GMP) map. The findings indicate that the GMP map has the potential to be used in real-time to quantify the absorbable energy, thus passivity margin of stability for upper limb interaction during pHRI

Cartesian impedance control of redundant manipulators for human-robot co-manipulation

This paper addresses the problem of controlling a robot arm executing a cooperative task with a human who guides the robot through direct physical interaction. This problem is tackled by allowing the end effector to comply according to an impedance control law defined in the Cartesian space. While, in principle, the robot's dynamics can be fully compensated and any impedance behaviour can be imposed by the control, the stability of the coupled human-robot system is not guaranteed for any value of the impedance parameters. Moreover, if the robot is kinematically or functionally redundant, the redundant degrees of freedom play an important role. The idea proposed here is to use redundancy to ensure a decoupled apparent inertia at the end effector. Through an extensive experimental study on a 7-DOF KUKA LWR4 arm, we show that inertial decoupling enables a more flexible choice of the impedance parameters and improves the performance during manual guidance

Whole-Body Control of a Mobile Manipulator for Passive Collaborative Transportation

Human-robot collaborative tasks foresee interactions between humans and robots with various degrees of complexity. Specifically, for tasks which involve physical contact among the agents, challenges arise in the modelling and control of such interaction. In this paper we propose a control architecture capable of ensuring a flexible and robustly stable physical human-robot interaction, focusing on a collaborative transportation task. The architecture is deployed onto a mobile manipulator, modelled as a whole-body structure, which aids the operator during the transportation of an unwieldy load. Thanks to passivity techniques, the controller adapts its interaction parameters online while preserving robust stability for the overall system, thus experimentally validating the architecture

On the passivity of interaction control with series elastic actuation

Regulating the mechanical interaction between robot and environment is a fundamentally important problem in robotics. Many applications such as manipulation and assembly tasks necessitate interaction control. Applications in which the robots are expected to collaborate and share the workspace with humans also require interaction control. Therefore, interaction controllers are quintessential to physical human-robot interaction (pHRI) applications. Passivity paradigm provides powerful design tools to ensure the safety of interaction. It relies on the idea that passive systems do not generate energy that can potentially destabilize the system. Thus, coupled stability is guaranteed if the controller and the environment are passive. Fortunately, passive environments constitute an extensive and useful set, including all combinations of linear or nonlinear masses, springs, and dampers. Moreover, a human operator may also be treated as a passive network element. Passivity paradigm is appealing for pHRI applications as it ensures stability robustness and provides ease-of-control design. However, passivity is a conservative framework which imposes stringent limits on control gains that deteriorate the performance. Therefore, it is of paramount importance to obtain the most relaxed passivity bounds for the control design problem. Series Elastic Actuation (SEA) has become prevalent in pHRI applications as it provides considerable advantages over traditional sti actuators in terms of stability robustness and delity of force control, thanks to deliberately introduced compliance between the actuator and the load. Several impedance control architectures have been proposed for SEA. Among the alternatives, the cascaded controller with an inner-most velocity loop, an intermediate torque loop and an outer-most impedance loop is particularly favoured for its simplicity, robustness, and performance. In this thesis, we derive the necessary and su cient conditions to ensure the passivity of the cascade-controller architecture for rendering two classical linear impedance models of null impedance and pure spring. Based on the newly established passivity conditions, we provide non-conservative design guidelines to haptically display free-space and virtual spring while ensuring coupled stability, thus the safety of interaction. We demonstrate the validity of these conditions through simulation studies as well as physical experiments. We demonstrate the importance of including physical damping in the actuator model during derivation of passivity conditions, when integral controllers are utilized. We note the unintuitive adversary e ect of actuator damping on system passivity. More precisely, we establish that the damping term imposes an extra bound on controller gains to preserve passivity. We further study an extension to the cascaded SEA control architecture and discover that series elastic damping actuation (SEDA) can passively render impedances that are out of the range of SEA. In particular, we demonstrate that SEDA can passively render Voigt model and impedances higher than the physical spring-damper pair in SEDA. The mathematical analyses of SEDA are veri ed through simulations

Evaluation and Comparison of SEA Torque Controllers in a Unified Framework

Series elastic actuators (SEA) with their inherent compliance offer a safe torque source for robots that are interacting with various environments, including humans. These applications have high requirements for the SEA torque controllers, both in the torque response as well as interaction behavior with its the environment. To differentiate state of the art torque controllers, this work is introducing a unifying theoretical and experimental framework that compares controllers based on their torque transfer behavior, their apparent impedance behavior, and especially the passivity of the apparent impedance, i.e. their interaction stability, as well as their sensitivity to sensor noise. We compare classical SEA control approaches such as cascaded PID controllers and full state feedback controllers with advanced controllers using disturbance observers, acceleration feedback and adaptation rules. Simulations and experiments demonstrate the trade-off between stable interactions, high bandwidths and low noise levels. Based on these tradeoffs, an application specific controller can be designed and tuned, based on desired interaction with the respective environment