International audience

This article presents the results of an experiment on physical Human-Human Interaction (pHHI), where human dyads cooperate on a one-dimensional comanipulative task in a novel lightweight teleoperation setup. The results of this experiment show that humans are able to handle asymmetrical information about the task and solve conflicts using only the kinesthetic channel. Data from the pHHI experiment is used to design a virtual partner that can perform the task alongside a human. The virtual partner behavior is based on the observation that initiative is highly correlated to decision-making in our pHHI negotiation scenario. The virtual agent is then evaluated in a physical Human-Robot Interaction (pHRI) experiment. The results of the second experiment show that the virtual partner is able to perform the task without compromising the performances of the dyad and that a similar role distribution is observed in human-human and human-robot dyads. Moreover, the knowledge of the partner’s nature does not seem to influence the performances. The results obtained with the virtual partner are encouraging and could be used to design kinesthetic negotiation algorithms in pHRI settings. The main contributions of this article are: (1) supporting evidence of the possibility for humans to use the kinesthetic channel as mean of negotiation during physical Human-Human Interaction in the lightest known impedance negotiation tasks (with no virtual mass involved), (2) highlighting of the correlation between initiative and dyadic decision making, (3) design of a simple yet efficient virtual partner algorithm capable of realistic physical Human-Robot Interaction in the one-dimension tracking task used in the experimental setup. This design combines minimum jerk trajectory, switching role ability, decision criteria, and statistical parameters that are detailed in this article.

The present paper investigates the relationship between human and virtual partners’ behaviors during a comanipulative task requiring negotiation. More precisely, the study is focused on the influence of the Virtual Partner’s (which was designed in a previous study) propensity to take the lead during conflicts over its human partner behavior. The experimental design includes both Human-Human and Human-Robot trials. The Human-Human trials serve as a baseline condition and help assessing the importance of the partner’s nature (human vs robot) knowledge in the subjects behavior. The Human-Robot trials are used to observe the effect of different tuning of the Virtual Partner on the dominance relationship within Human-Robot dyads. The results of the study show that Human behavior is consistent across Human-Human trials, and is not influenced by the knowledge of their partner’s nature. Moreover, a simple tuning of the negotiation thresholds of the Virtual Partner allows to significantly modify the dominance of the human partner, although this modification has no lasting effects.

The present paper investigates if and in which conditions does the implementation of high stiffness controllers increase the performances of human dyads during comanipulative tasks in physical Human-Human Interaction (pHHI) settings. Two experiments are conducted which cover two fundamental aspects of pHHI: low-level interactions allowing interpersonal coordination, and high-level interactions allowing common decision-making and negotiation of strategies. The results of these experiments show that high stiffness is not necessary for good performances when the task only requires low-level interactions. On the contrary, when dealing with high-level interactions, higher stiffness increases task performance. The results presented highlight the importance of the quality of teleoperated control in setups used for the study of pHHI.

This paper presents an experimental evaluation of physical human-human interaction in lightweight condition using a one degree of freedom robotized setup. It explores possible origins of Physical Human-Human communication, more precisely, the hypothesis of a time based communication. To explore if the communication is correlated to time a, statistical state machine model based on physical Human-Human interaction is proposed. The model is tested with 14 subjects and presents results that are close to human-human performances.

Assisted gait monitoring could benefit from the measurement of feet position and orientation. These measurements could also be used to implement intention-based control laws for smart walkers. Several works have been dedicated to the detection of lower limbs. The proposed methods are usually fast, but only detect the position of the legs. Others may even be more complete, but are not adapted to reactive applications. Also, they often use markers attached on the feet, which is unsuitable in daily routine. In this paper, a fast feet position and orientation detection algorithm is proposed. It is based on a camera depth sensor and does not require the use of any marker. The obtained results are compared with a ground truth provided by a motion traking system to experimentally assess the performances of the proposed algorithm.

This paper presents clinical results from the use of monitor-nomad (MONIMAD), which is a reactive robotized interface for lower limb rehabilitation of patients suffering from cerebellar disease. The first problem to be addressed is the postural analysis of sit-to-stand motion. Experiments with healthy subjects were performed for this purpose. Analysis of external forces shows that sit-to-stand transfer can be subdivided into several phases: preacceleration, acceleration, start rising, and rising. Observation of center of pressure, ground forces, and horizontal components force on handles yields rules that identify the stability of the patient and adjust the robotic interface motion to the human voluntary movement. These rules are used in a fuzzy-based controller implementation. The controller is validated on experiments with diseased patients at Bellan Hospital, Paris, France.

Measuring human movement in real time is of primary importance in a number of new applications of interactive systems and human centered robotics. A major difficulty in this field arises from the high joint redundancy of the human kinematics. Conventional approaches address this problem by installing a rather large number of sensors or markers on the subject. On the other hand, well admitted theories in neurosciences claim that joint synchronization in human movements is governed by so-called synergies, that can be viewed as joint patterns corresponding to a given gesture of a given individual. In this paper, we intend to exploit this property in order to reduce the number of sensors to be installed on a human subject when tracking his/her motion. Namely, our suggested method comprizes two phases. In a learning stage, the subject is asked to complete a given gesture a few times, while he/she is equipped with sensors able to measure his/her full posture. An algorithm is thus used in a second phase to reduce the required number of sensors while reconstructing the whole posture of the subject. Experimental evidence is provided for the particular motion of sit-to-stand transfer, in a study that involves healthy subjects.

The aim of the work presented in this paper is to realize the model for the control of a robotic interface for equilibrium assistance during sit-to-stand transfer. Interactive robotic devices designed as human-centered robotics, can give more comfortable and more efficient solutions than traditional technical devices. One supposes the need of a virtual model of the pathology. This model, called observer, aims at being used in the smoothing control part of this assisting device. A useful property of this observer should be a postural prediction ability. This article presents a study of different neural solutions : a Neural Predictive Observer (NPO) and a Reduced Neural Predictive Observer (RNPO). Records used for the learning have been done from healthy people that stand up normally and quickly. Some tests will also be done in patients with cerebellar syndrome disease. The presented experimental results show the good accuracy of these approaches whatever the speed of the movement.