Physical Human-Robot Interaction

An integrated network of mobile robots, personal smart devices, and smart spaces called " Robots-Assisted Ambient Intelligence " (RAmI) can provide for a more effective user assistance than if the former resources are used individually. Additionally, with the application of distributed network optimization, not only can we improve the assistance of an individual user, but we can also minimize conflict or congestion created when multiple users in large installations use the limited resources of RAmI that are spatially and temporally constrained. The emphasis of RAmI is on the efficiency and effectiveness of multiple and simultaneous user assistance and on the influence of an individual's actions on the desired system's performance. In this paper, we model RAmI as a multi-agent system with AmI, user, and robot agents. Moreover, we propose a modular three-layer architecture for each robot agent and discuss its application and communication requirements to facilitate efficient usage of limited RAmI resources. Our approach is showcased by means of a case study where we focus on meal and medicine delivery to patients in large hospitals.

The methods required to make humans and robots interact and collaborate are the subject of research in physical human-robot interaction (pHRI). One of the main issues, particularly when physical contact can occur between the two, is safety. A second fundamental requirement to establish pHRI is intuitive control by the human operator, in particular when s/he is non expert. Sensor-based control can address both issues, by closing the perception-to-action loop, in a way that may well be assimilated to that of the lower motor neurons in our nervous system. Traditionally, heterogeneous sensor data was fed to fusion algorithms (e.g., Kalman or Bayesian-based), so as to provide state estimation for modeling the environment. However, since robot sensors generally measure different physical phenomena, it is preferable to use them directly in the low-level servo controller rather than to apply them to multi-sensory fusion or to design complex state machines. This idea, originally proposed in the hybrid position-force control paradigm, when extended to multiple sensors brings new challenges to the control design; challenges related to the task representation and to the sensor characteristics (synchronization, hybrid control, task compatibility, etc.). The rationale behind my work has precisely been to use sensor-based control as a means to facilitate the physical interaction between robots and humans. In particular, I have utilized vision, proprioceptive force, touch and distance to address pHRI case studies, targeting different applications and robot platforms. My research has followed four main axes: teach-and-repeat navigation of wheeled mobile robots, collaborative industrial manipulation with safe physical interaction, force and visual control for interacting with humanoid robots, and shared robot control. Each of these axes will be presented here, before concluding with a general view of the issues at stake, and on the research projects that I plan to carry out in the upcoming years.

In this paper, we present a novel robotic system that produces watercolour paintings by means of a 6-degree-of-freedom collaborative robot. After an analysis of traditional watercolour, different non-photorealistic rendering techniques are applied in order to elaborate digital images into artworks. Several algorithms, aimed at processing both the backgrounds and the details, are implemented. Then, the resulting rendering is converted into a sequence of trajectories that the robot reproduces on paper. During the process, the artist controlling the system can change both the algorithm parameters and the hardware variables (e.g. brush type, colour dilution, etc.) in order to obtain a different artistic rendering. The challenge is indeed not to faithfully reproduce an image but to introduce a personal and original contribution to the artwork. The robotic painting system described in this paper was named "Busker Robot" and it is the first automatic system that uses the watercolour technique for artistic rendering. It was installed at the "Algorithmic Arts and Robotics" exhibition during the international event "Trieste Next" (Trieste, Italy, September 2017) and won an Honorable Mention at the 2018 International Robotic Art Competition (RobotArt).

In the framework of physical human-robot interaction (pHRI), methodologies and experimental tests are presented for the problem of detecting and reacting to collisions between a robot manipulator and a human being. Using a lightweight robot that was especially designed for interactive and cooperative tasks, we show how reactive control strategies can significantly contribute to ensuring safety to the human during physical interaction. Several collision tests were carried out, illustrating the feasibility and effectiveness of the proposed approach. While a subjective ldquosafetyrdquo feeling is experienced by users when being able to naturally stop the robot in autonomous motion, a quantitative analysis of different reaction strategies was lacking. In order to compare these strategies on an objective basis, a mechanical verification platform has been built. The proposed collision detection and reactions methods prove to work very reliably and are effective in reducing contact forces far below any level which is dangerous to humans. Evaluations of impacts between robot and human arm or chest up to a maximum robot velocity of 2.7 m/s are presented.

Haptic paddles — low-cost one-degree-of-freedom force feedback devices — have been used with great success at several universities throughout the United States to teach the basic concepts of dynamic systems and physical human-robot interaction (pHRI) to students. The ETHZ haptic paddle was developed for a new pHRI course offered in the undergraduate Mechatronics Focus track of the Mechanical Engineering curriculum at ETH Zurich, Switzerland. Twenty students engaged in this two-hour weekly lecture over the 14 weeks of the autumn 2011 semester, complemented by a weekly two-hour laboratory session with the ETHZ haptic paddle. In pairs, students worked through three common sets of experiments before embarking on a specialization project that investigated one of several advanced topics such as impedance control with force feedback, admittance control, the effect of velocity estimation on stability or electromyographic control. For these projects students received additional hardware, including force sensors, electro-optical encoders or high-performance data acquisition cards. The learning objectives were developed in the context of an accompanying faculty development program at ETH Zurich; a set of interactive sequences and the oral exam were explicitly aligned to these learning objectives. The outcomes of the specialization project presentations and oral exams, and a student evaluation of the course, demonstrated that the ETHZ haptic paddle is a valuable tool that allows students to quite literally grasp abstract principles such as mechanical impedance, passivity and human factors, and helps students create a tangible link between theory and practice in the highly interdisciplinary field of pHRI.

Human language is inherently embodied and grounded in sensorimotor representations of the self and the world around it. This suggests that the body schema and ideomotor action-effect associations play an important role in language understanding, language generation, and verbal/physical interaction with others. There are computational models that focus purely on non-verbal interaction between humans and robots, and there are computational models for dialog systems that focus only on verbal interaction. However, there is a lack of research that integrates these approaches. We hypothesize that the development of computational models of the self is very appropriate for considering joint verbal and physical interaction. Therefore, they provide the substantial potential to foster the psychological and cognitive understanding of language grounding, and they have significant potential to improve human-robot interaction methods and applications. This review is a first step toward developing models of the self that integrate verbal and non-verbal communication. To this end, we first analyze the relevant findings and mechanisms for language grounding in the psychological and cognitive literature on ideomotor theory. Second, we identify the existing computational methods that implement physical decision-making and verbal interaction. As a result, we outline how the current computational methods can be used to create advanced computational interaction models that integrate language grounding with body schemas and self-representations.

ABSTRACT In human-robot interaction, the robot controller must reactively adapt to sudden changes in the environment (due to unpredictable human behaviour). This often requires operating different modes, and managing sudden signal changes from heterogeneous sensor data. In this paper, we present a multimodal sensor-based controller, enabling a robot to adapt to changes in the sensor signals (here, changes in the human collaborator behaviour). Our controller is based on a unified task formalism, and in contrast with classical hybrid vision-force-position control, it enables smooth transitions and weighted combinations of the sensor tasks. The approach is validated in a mock-up industrial scenario, where pose, vision (from both traditional camera and Kinect), and force tasks must be realized either exclusively or simultaneously, for human-robot collaboration.

Human-robot interaction (HRI) is fundamental for human-centered robotics, and has been attracting intensive research for more than a decade. The series elastic actuator (SEA) provides inherent compliance, safety and further benefits for HRI, but the introduced elastic element also brings control difficulties. In this paper, we address the stiffness rendering problem for a cable-driven SEA system, to achieve either low stiffness for good transparency or high stiffness bigger than the physical spring constant, and to assess the rendering accuracy with quantified metrics. By taking a velocity-sourced model of the motor, a cascaded velocity-torque-impedance control structure is established. To achieve high fidelity torque control, the 2-DOF (degree of freedom) stabilizing control method together with a compensator has been used to handle the competing requirements on tracking performance, noise and disturbance rejection, and energy optimization in the cable-driven SEA system. The conventional passivity requirement for HRI usually leads to a conservative design of the impedance controller, and the rendered stiffness cannot go higher than the physical spring constant. By adding a phase-lead compensator into the impedance controller, the stiffness rendering capability was augmented with guaranteed relaxed passivity. Extensive simulations and experiments have been performed, and the virtual stiffness has been rendered in the extended range of 0.1 to 2.0 times of the physical spring constant with guaranteed relaxed passivity for physical humanrobot interaction below 5 Hz. Quantified metrics also verified good rendering accuracy.

Robots designed to share an environment with humans, such as e.g. in domestic or entertainment applications or in cooperative material-handling tasks, must fulfill different requirements from those typically met in industry. It is often the case, for instance, that accuracy requirements are less demanding. On the other hand, concerns of paramount importance are safety and dependability of the robot system. According to such difference in requirements, it can be expected that usage of conventional industrial arms for anthropic environments will be far from optimal. An approach to increase the safety level of robot arms interacting with humans consists in the introduction of compliance at the mechanical design level. In this paper we discuss the problem of achieving good performances in accuracy and promptness with a robot manipulator under the condition that safety is guaranteed throughout whole task execution. Intuitively, while a rigid and powerful structure of the arm would favor its performance, lightweight compliant structures are more suitable for safe operation. The quantitative analysis of the resulting design trade-off between safety and performance has a strong impact on how robot mechanisms and controllers should be designed for human- interactive applications. We discuss few different possible concepts for safely actuating joints, and focus on aspects related to the implementation of the mechanics and control of this new class of robots.

The paper focuses on the teleoperation system TeleTA with haptic feedback designed to realize haptic communication with remote human, to achieve high level of maneuverability of robot arm in unstructured environment, and to increase effectiveness of physical human-robot interaction. The human operator directs the robot arm to the target position, while manipulator sensory system provides safe physical interaction with environment.