Aurélie Clodic

Task planning for human-robot interaction

Human-robot interaction requires explicit reasoning on the human environment and on the robot capacities to achieve its tasks in a collaborative way with a human partner.This paper focuses on organization of the robot decisional abilities and more particularly on the management of human interaction as an integral part of the robot control architecture. Such an architecture should be the framework that will allow the robot to accomplish its tasks but also produce behaviors that support its engagement vis-a-vis its human partner and interpret similar behaviors from him.Together and in coherence with this framework, we intend to develop and experiment various task planners and interaction schemes, that will allow the robot to select and perform its tasks while taking into account explicitly the constraints imposed by the presence of humans, their needs and preferences.We have considered a scheme where the robot plans for itself and for the human in order not only (1) to assess the feasibility of the task (at a certain level) before performing it, but also (2) to share the load between the robot and the human and (3) to explain/illustrate a possible course of action.

Using controller-synthesis techniques to build property-enforcing layers

In complex systems, like robot plants, applications are built on top of a set of components, or devices. Each of them has particular individual constraints, and there are also logical constraints on their interactions, related to e.g., mechanical characteristics or access to shared resources. Managing these constraints may be separated from the application, and performed by an intermediate layer. We show how to build such property-enforcing layers, in a mixed imperative/ declarative style: 1) the constraints intrinsic to one component are modeled by an automaton; the product of these automata is a first approximation of the set of constraints that should be respected; 2) the constraints that involve several components are expressed as temporal logic properties of this product; 3) we use general controller synthesis techniques and tools in order to combine the set of communicating parallel automata with the global constraint.

Supervision and motion planning for a mobile manipulator interacting with humans

Human Robot collaborative task achievement requires adapted tools and algorithms for both decision making and motion computation. The human presence as well as its behavior must be considered and actively monitored at the decisional level for the robot to produce synchronized and adapted behavior. Additionally, having a human within the robot range of action introduces security constraints as well as comfort considerations which must be taken into account at the motion planning and control level. This paper presents a robotic architecture adapted to human robot interaction and focuses on two tools: a human aware manipulation planner and a supervision system dedicated to collaborative task achievement.

Rackham: An Interactive Robot-Guide

Rackham is an interactive robot-guide that has been used in several places and exhibitions. This paper presents its design and reports on results that have been obtained after its deployment in a permanent exhibition. The project is conducted so as to incrementally enhance the robot functional and decisional capabilities based on the observation of the interaction between the public and the robot. Besides robustness and efficiency in the robot navigation abilities in a dynamic environment, our focus was to develop and test a methodology to integrate human-robot interaction abilities in a systematic way. We first present the robot and some of its key design issues. Then, we discuss a number of lessons that we have drawn from its use in interaction with the public and how that will serve to refine our design choices and to enhance robot efficiency and acceptability

SHARY: A Supervision System Adapted to Human-Robot Interaction

Human-Robot Interaction (HRI) brings new challenges to robotics. We focus in this paper on the decisional issues of HRI enabled robots. We propose a control architecture specifically designed for HRI and present an implemented system that illustrates its main components and their interaction. These components provide integrated abilities to support human-robot collaborative task achievement as well as capacities to elaborate task plans involving humans and robots and to produce legible and socially acceptable behavior.

Implementing a Human-Aware Robot System

The presence of humans in the robot environment brings new challenges to the robotic research. From low level functions to high level planners, clearly the human has to be taken into account in all the layers of the robot control system. Indeed, the robot has to behave socially in order to interact friendly with its human partners. This paper describes the development of several components (human detection and tracking, planning and supervision) that take into account humans explicitly with some preliminary results of their integration

A study of interaction between dialog and decision for human-robot collaborative task achievement

Human-robot collaboration requires both communicative and decision making skills of a robot. To enable flexible coordination and turn-taking between human users and a robot in joint tasks, the robots dialog and decision making mechanism have to be synchronized in a meaningful way. In this paper, we propose a integration framework to combine the dialog and the decision making processes. With this framework, we investigate various task negotiation situations for a social robot in a fetch-and-carry scenario. For the technical realization of the framework, the interface specification between the dialog and the decision making systems is also presented. Further, we discuss several challenging issues identified in our integration effort that should be addressed in the future.

A decisional framework for autonomous robots interacting with humans

The presence of humans in its environment and the necessity to interact with them raise new challenges to the robot. Indeed, they require explicit reasoning on the human environment and on the robot capacities to achieve its tasks in a collaborative way with a human partner. This paper focuses on architectural aspects and more particularly on the organization of the robot decisional abilities for interacting with people. Indeed, our objective is to develop a management of human interaction that would be an integral part of a general robot control architecture. This should hopefully allow to come up with a principled way to deal with human-robot interaction for robot task achievement in presence of humans or in synergy with humans. Such an architecture should be the framework that would allow the robot to produce behaviors to accomplish its tasks but also produce behaviors that support its engagement vis-a-vis its human partner and interpret similar behaviors from him. We also intend to use the proposed approach as a framework in which we would develop and experiment various task planners and interaction schemes. Indeed, the robot should be able, for instance, to devise plans that allow it to execute its actions and to place itself to be seen by or to observe humans, according to the task.

On Planning and Task Achievement Modalities for Human-Robot Collaboration

In this paper we present a robot supervision system designed to be able to execute collaborative tasks with humans in a flexible and robust way. Our system is designed to take into account the different preferences of the human partners, providing three operation modalities to interact with them. The robot is able to assume a leader role, planning and monitoring the execution of the task for itself and the human, to act as assistent of the human partner, following his orders, and also to adapt its plans to the human actions. We present several experiments that show that the robot can execute collaborative tasks with humans.

Supervision and interaction

This paper presents the design and the implementation of a new tour-guide robot and reports on the first results that have been obtained after its deployment in a permanent exhibition. The project is conducted so as to incrementally enhance the robot functional and decisional capabilities based on the observation of the interaction between the public and the robot. Besides robustness and efficiency in the robot basic navigational abilities in a dynamic environment, our focus was to develop and test a methodology to integrate human-robot interaction abilities in a systematic way. We first present the robot and some of its key design issues. Then, we discuss a number of lessons that we have drawn from its use in interaction with the public and how that serve to refine our design choices and to enhance the robot efficiency and acceptability