Giancarlo Teti

An experimental study on compliance control for a redundant personal robot arm

Abstract Human–robot interaction represents a critical factor in the design of personal robots as well as in the implementation of robot behavior and control. This work investigates and proposes solutions to the problem of controlling an anthropomorphic robot arm for personal assistance, by dealing with the peculiarities of its design, i.e. the mechanics of its cable-actuated, intrinsically compliant structure, and by emphasizing its potential in applications of physical and functional interaction with the environment and with human users. To satisfy the requirements of increasing the safety in the interaction and the robot functionality in tasks performed in cooperation with humans, three solutions are developed and tested for the considered personal robot. The initial idea is aimed at developing an efficient as well as computational convenient interaction control strategy, i.e. a compliance control scheme in the Cartesian space. The analysis of its limited performance suggests two further control strategies, i.e. a compliance control scheme in the joint space and an impedance–compliance control scheme. Their compared analysis points out that all the three solutions can safely operate in the human environment, but from a functional point of view only the last two schemes can effectively control the personal robot arm in its whole workspace. The paper describes the mechanics of the considered robot arm, with special regard to its anthropomorphism and cable-actuation and presents in details the three control schemes. They are critically evaluated through the experimental results achieved in tasks of physical and functional interaction with the environment and with human users. The impedance–compliance controller emerges as the more appropriate to the addressed application as well as to the peculiar cable-actuated structure.

Development of a Socially Believable Multi-Robot Solution from Town to Home

Abstract Technological advances in the robotic and ICT fields represent an effective solution to address specific societal problems to support ageing and independent life. One of the key factors for these technologies is that they have to be socially acceptable and believable to the end-users. This paper aimed to present some technological aspects that have been faced to develop the Robot-Era system, a multi-robotic system that is able to act in a socially believable way in the environments daily inhabited by humans, such as urban areas, buildings and homes. In particular, this paper focuses on two services—shopping delivery and garbage collection—showing preliminary results on experiments conducted with 35 elderly people. The analysis adopts an end-user-oriented perspective, considering some of the main attributes of acceptability: usability, attitude, anxiety, trust and quality of life.

Adaptable semi-autonomy in personal robots

Personal robotics is widely recognized as a major challenge for current robotics research. Robots assisting humans and closely interacting with them have to meet acceptability requirements which in turn leads one to reconsider the concept of autonomy in robotics. The paper presents an abstract analysis of possible levels of semi-autonomy in personal robots and illustrates a case study in which adaptable semi-autonomy is implemented and experimentally validated. Explanation modules for human-robot communication in the planning phase, and user modeling techniques, that allow the system to adapt to its users needs and preferences, are proposed as ways to achieve adaptive semi-autonomy.

Expected perception: an anticipation-based perception-action scheme in robots

The paper proposes an anticipation mechanism to improve the perception-action loop of robots interacting with real-world environments. According to recent neuroscientific findings, sensory anticipation can increase the effectiveness of perception-action loops and reduce the delays in obtaining the sensory information, especially in case of complex sensory modalities like vision, that affect pure feed-back structures. In the proposed scheme, perception crucially involves comparison processes between incoming stimuli and expected perceptions (EPs), built from previous perceptions, current motor commands, and internal models of the robot and the environment. Background knowledge plays here a helpful role, as it reduces the computational burden of perception and motor coordination tasks in partially structured environments. In the work presented here, an EP mechanism has been applied in the visuo-motor coordination of an anthropomorphic 8 d.o.f. robotic manipulator equipped with a vision system, in order to evaluate the conditions of applicability of the proposed strategy, and to validate the viability and effectiveness of the initial hypothesis.

A bio-inspired predictive sensory-motor coordination scheme for robot reaching and preshaping

Abstract This paper presents a sensory-motor coordination scheme for a robot hand-arm-head system that provides the robot with the capability to reach an object while pre-shaping the fingers to the required grasp configuration and while predicting the tactile image that will be perceived after grasping. A model for sensory-motor coordination derived from studies in humans inspired the development of this scheme. A peculiar feature of this model is the prediction of the tactile image. The implementation of the proposed scheme is based on a neuro-fuzzy module that, after a learning phase, starting from visual data, calculates the position and orientation of the hand for reaching, selects the best-suited hand configuration, and predicts the tactile feedback. The implementation of the scheme on a humanoid robot allowed experimental validation of its effectiveness in robotics and provided perspectives on applications of sensory predictions in robot motor control.

Compliant control for a cable-actuated anthropomorphic robot arm: an experimental validation of different solutions

This paper presents a research work on compliant control of an anthropomorphic robot arm used as a personal robot. In personal applications of robotics, human-robot interaction represents a critical factor for a robot design and introduces strict requirements on its behavior and control, which has to ensure safety and effectiveness. In this work, the problem of controlling the Dexter anthropomorphic robot arm with variable compliance has been investigated, not only to ensure safety in the interaction with humans, but especially to increase the robot functionality in tasks of physical interaction, performed in co-operation with humans. Two different control schemes have been formulated and implemented, to compare their performance experimentally. Both schemes aim at realising a self-controlled compliant behavior without using information from force/torque sensors. The experimental comparison outlines how the performance of the two control systems are inverted with respect to the theoretical considerations, based on the classical control theory, on their accuracy and effectiveness.

Functional compliance in the control of a personal robot

The research in the field of advanced robotics is turning its attention more and more to man and his assistance, by developing systems such as service robots, personal robots, and even humanoid robots. Interaction control of such robot manipulators is of paramount importance for an effective execution of manipulation and tracking and, over all, for a safe and effective interaction with the humans. The paper concerns the problem of the control of an 8 degree of freedom anthropomorphic arm named DEXTER, mounted on the mobile platform of the MOVAID System, a robotic system for household personal assistance. The goal is to realize a compliant control for this manipulator in tasks of assistance to disabled and elderly people. On the basis of the control theory applied to industrial robotics, a specific compliant control solution has been developed for the DEXTER peculiar mechanical structure and actuation system, which cause a coupled joint configuration. The solution provides the capability of regulating the robot compliance according to the level of stiffness of the interaction environment. The paper describes the theoretical model of the control system, the implementation on the MOVAID platform and the experimental results in the execution of a set of demonstration tasks.

An anthropomorphic robotic platform for experimental validation of biologically-inspired sensory-motor co-ordination in grasping

The aim of the work is the integration of an anthropomorphic robotic platform, starting from a neurophysiological model of grasping, in order to provide tools for an experimental validation of the model and also to provide new anthropomorphic solutions for robot grasping. The resulting robotic system is composed of an anthropomorphic arm/hand system and visual and tactile sensors. Grasp planning, control and learning have been achieved by a neural approach, inspired by a model of the inter-connections among the brain areas involved in grasping, as formulated by neurophysiologists. After a description of objectives and specifications for the robotic platform, the system is illustrated and experimental results are reported. Finally, the results are discussed as a starting point for current activities, involving the development of novel human-like robotic components and the implementation of more sophisticated learning schemes.

A Bio-inspired Neural Sensory-Motor Coordination Scheme for Robot Reaching and Preshaping

We present a sensory-motor coordination scheme for a robot hand-arm-head system that provides the robot with the capability to reach for and to grasp an object, while pre-shaping the fingers to the required grasp configuration. A model for sensory-motor coordination derived from studies in humans inspired the development of the scheme. A special feature of this model is the prediction of the tactile image perceived after grasping. The proposed scheme is based on a neuro-fuzzy module that, after a learning phase, starting from visual data, calculates the position and orientation of the hand for grasping, selects the best-suited hand configuration, and predicts the tactile feedback after grasping. The implementation of the scheme on a humanoid robot allowed experimental validation of its effectiveness in robotics and provided perspectives on applications of sensory predictions in robot motor control

An Investigation on Legal Regulations for Robot Deployment in Urban Areas: A Focus on Italian Law

This paper investigates the administrative, criminal and civil aspects of Italian law in order to find out whether and how current legal regulations impact on robot deployment in urban environments. The paper is based on a case study. The objects of this study are two autonomous mobile robots designed to carry out urban hygiene services in pedestrian areas. The paper points out a major problem in Italian law — the lack of legal qualification for autonomous mobile robots operating on public roads. On the contrary, at present, no relevant implications are identified with regard to Italian criminal and civil law. As a matter of fact, although autonomous, the robots that are at the center of this study can still be considered as properties and, therefore, are excluded from any personal liability in case of damage to people or things.