Paul Evrard

Homotopy switching model for dyad haptic interaction in physical collaborative tasks

The main result of this paper is a new model based on homotopy switching between intrinsically distinct controllers that encompass most behaviors encountered in dyadic haptic collaborative tasks. The basic idea is to switch continuously between two distinct extreme behaviors (leader and follower) for each individual, which creates an implicit bilateral coupling within the dyad. The physical collaborative interaction is then described only with two distinct homotopy time-functions that vary independently. These functions can likely describe the signature of a collaborative task. A virtual reality haptic set-up is used to assess the proposed theory.

Teaching physical collaborative tasks: object-lifting case study with a humanoid

This paper presents the application of a statistical framework that allows to endow a humanoid robot with the ability to perform a collaborative manipulation task with a human operator. We investigate to what extent the dynamics of the motion and the haptic communication process that takes place during physical collaborative tasks can be encapsulated by the probabilistic model. This framework encodes the dataset in a Gaussian Mixture Model, which components represent the local correlations across the variables that characterize the task. A set of demonstrations is performed using a bilateral coupling teleoperation setup; then the statistical model is trained in a pure follower/leader role distribution mode between the human and robot alternatively. The task is reproduced using Gaussian Mixture Regression. We present the probabilistic model and the experimental results obtained on the humanoid platform HRP-2; preliminary results assess our theory on switching behavior modes in dyad collaborative tasks: when reproduced with users which were not instructed to behave in either a follower or a leader mode, the robot switched automatically between the learned leader and follower behaviors.

Real-time (self)-collision avoidance task on a hrp-2 humanoid robot

This paper proposes a real-time implementation of collision and self-collision avoidance for robots. On the basis of a new proximity distance computation method which ensures having continuous gradient, a new controller in the velocity domain is proposed. The gradient continuity encompasses no jump in the generated command. Included in a stack of tasks architecture, this controller has been implemented on the humanoid platform HRP-2 and experienced in a grasping task while walking and avoiding collisions with the environment and auto-collisions.

Framework for haptic interaction with virtual avatars

In this paper we present an integrative frame work centered on haptic interaction with virtual avatars. This framework is devised for general prototyping and collaborative scenario studies with haptic feedback. First we present the software architecture of the framework and give details on some of its components. Then we show how this framework can be used to derive in a short time a virtual reality simulation. In this simulation, a user directly interacts with a virtual avatar to collaboratively manipulate a virtual object, with haptic feedback and using fast dynamics computation and constraint based methods with friction.

Homotopy-based controller for physical human-robot interaction

This paper presents a model that describes physical interactions during dyadic collaborative tasks. This model is based on a homotopy between two controllers and defines the behavior of each partner as the result of a time-varying balance between two roles: the leader role, which consists in acting according to a plan without considering the other partners intentions; and the follower role, which conversely consists in acting only based on the intentions of the other partner. The continuous switch between these two attitudes is described by two variables whose time-profile can define a task signature. After a brief presentation of the model, two illustrative scenarios are detailed to give more insights on how the homotopy parameter can be used to describe different situations that can occur in collaborative tasks between two partners. We especially focus on how some recent results in the human-human interaction can be encompassed by our proposed model. Experiments are performed to assess the usability of the model as a control scheme to implement advanced collaborative behaviors on a robotic platform.

Interactive dynamics and balance of a virtual character during manipulation tasks

This paper proposes a new framework of online hybrid control for virtual characters, which combines multi-objective control and motion capture techniques. At each time step, the motions of the operator are captured and sent to the character. These captured motions help the character understand what task the operator wants it to perform. Then, the character decides by itself how to execute proper actions while maintaining its balance, in a virtual environment which is different from the real world. Given a manipulation task, the desired virtual task wrench is computed thanks to a force control approach. The control system takes these task wrenches into consideration and solves a constrained quadratic problem for joint torques, which are then used to drive the virtual character. The whole control problem is solved online so that the virtual character can interact in real-time with the virtual environment as well as the operator. Examples using this control framework are presented as results from simulation.

Modular Architecture for Humanoid Walking Pattern Prototyping and Experiments

In this paper we describe the use of design patterns as a basis for creating humanoid walking pattern generator software having a modular architecture. This architecture enabled the rapid porting of several novel walking algorithms on a full-size humanoid robot, HRP-2. The body of work currently available allows extracting a general software architecture usable with inter-exchange between simulations and real experiments. The proposed architecture with the associated design patterns is described together with several applications: a pattern generator for a HRP-2 with passive toe joints, a pattern for dynamically stepping over large obstacles and a new quadratic problem (QP) formulation for the generation of the reference zero-momentum point. Thanks to the versatility and the modularity of the proposed framework, the QP method has been implemented and experienced within 4 days only.

Intercontinental multimodal tele-cooperation using a humanoid robot

In multimodal tele-cooperation as considered in this paper two humans in distant locations jointly perform a task requiring multimodal including haptic feedback. One human operator teleoperates a remotely placed humanoid robot which is collocated with the human cooperator. Time delay in the communication channel as destabilizing factor is one of the multiple challenges associated with such a tele-cooperation setup. In this paper we employ a control architecture with force-position exchange accounting for the admittance type of the haptic input device and the telerobot, which both are position-based admittance controlled. Llewellynpsilas stability criteria are employed for the parameter tuning of the virtual impedances in the presence of time delay. The control strategy is successfully validated in an intercontinental tele-cooperation experiment with the humanoid telerobot HRP-2 located in Japan/Tsukuba and a multimodal human-system-interface located in Germany/Munich, see also the corresponding video submission. The proposed setup gives rise to a large number of exciting new research questions to be addressed in the future.

Intercontinental, multimodal, wide-range tele-cooperation using a humanoid robot

This paper is the continuation of our previous work in intercontinental, collaborative teleoperation with a humanoid robot. Our new achievement consists in an extension of the former single-arm bilateral teleoperation setting to include bimanual manipulation and walking. A coupling scheme for simultaneous manipulation and locomotion is developed. Furthermore, a task-based control framework, including a force-based control for the arms as well as a walking pattern generation, is presented to realize stable whole-body motions of the highly redundant humanoid robot. Experiments have been performed to assess the proposed control scheme. They bring to light additional scientific challenges that remain in order to reach a smooth and natural telepresent collaboration.

Task-driven posture optimization for virtual characters

This paper presents a generic approach to find optimal postures, including contact positions, for manipulation tasks. It can be used in either the preparation for a task, or the evaluation of the feasibility of a task during planning stages. With such an approach, an animator can control a virtual character from a high level by just specifying a task, such as moving an object along a desired path to a desired position; the animator does not need to manually find suitable postures for the task. For each task, an optimization problem is solved, which considers not only geometric and kinematic constraints, but also force and moment constraints. The optimized postures allow the virtual character to apply manipulation forces as strongly as possible, and meanwhile to avoid foot slipping. Moreover, potential perturbation forces can be taken into account in the optimization to make postures more robust. The realism of our approach is demonstrated with different types of manipulation tasks.