Emrah Akin Sisbot

A Human Aware Mobile Robot Motion Planner

Robot navigation in the presence of humans raises new issues for motion planning and control when the humans must be taken explicitly into account. We claim that a human aware motion planner (HAMP) must not only provide safe robot paths, but also synthesize good, socially acceptable and legible paths. This paper focuses on a motion planner that takes explicitly into account its human partners by reasoning about their accessibility, their vision field and their preferences in terms of relative human-robot placement and motions in realistic environments. This planner is part of a human-aware motion and manipulation planning and control system that we aim to develop in order to achieve motion and manipulation tasks in the presence or in synergy with humans.

Navigation in the presence of humans

Robot navigation in the presence of humans raises new issues for motion planning and control since the humans safety and comfort must be taken explicitly into account. We claim that a human-aware motion planner must not only elaborate safe robot paths, but also plan good, socially acceptable and legible paths. Our aim is to build a planner that takes explicitly into account the human partner by reasoning about his accessibility, his vision field and potential shared motions. This paper focuses on a navigation planner that takes into account the humans existence explicitly. This planner is part of a human-aware motion and manipulation planning and control system that we aim to develop in order to achieve motion and manipulation tasks in a collaborative way with the human. We are conducting research in a multidisciplinary perspective, (1) running user studies and (2) developing an algorithmic framework able to integrate knowledge acquired through the trials. We illustrate here a first step by implementing a human-friendly approach motion by the robot

A Human-Aware Manipulation Planner

With recent advances in safe and compliant hardware and control, robots are close to finding their places in our homes. As the safety barrier between humans and robots is beginning to fade, the necessity to design pertinent robot behavior in human environments is becoming a crucial step. In order to obtain a safe, comfortable, and socially acceptable interaction, the robot should be engineered from top to bottom by considering the presence of the human. In this paper, we present a manipulation planning framework and its implementation human-aware manipulation planner. This planner generates paths not only safe but comfortable and “socially acceptable” as well by reasoning explicitly on humans kinematics, vision field, posture, and preferences. The planner, which is applied into “robot handing over an object” scenarios, breaks the human centric interaction that depends mostly on human effort and allows the robot to take initiative by computing automatically where the interaction takes place, thus decreasing the cognitive weight of interaction on human side.

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.

Towards a Platform-Independent Cooperative Human Robot Interaction System: III An Architecture for Learning and Executing Actions and Shared Plans

Robots should be capable of interacting in a cooperative and adaptive manner with their human counterparts in open-ended tasks that can change in real-time. An important aspect of the robot behavior will be the ability to acquire new knowledge of the cooperative tasks by observing and interacting with humans. The current research addresses this challenge. We present results from a cooperative human-robot interaction system that has been specifically developed for portability between different humanoid platforms, by abstraction layers at the perceptual and motor interfaces. In the perceptual domain, the resulting system is demonstrated to learn to recognize objects and to recognize actions as sequences of perceptual primitives, and to transfer this learning, and recognition, between different robotic platforms. For execution, composite actions and plans are shown to be learnt on one robot and executed successfully on a different one. Most importantly, the system provides the ability to link actions into shared plans, that form the basis of human-robot cooperation, applying principles from human cognitive development to the domain of robot cognitive systems.

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.

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

Towards shared attention through geometric reasoning for Human Robot Interaction

Human Robot Interaction brings new challenges to the geometric reasoning and space sharing. The robot should not only reason on its own capacities but also consider the actual situation by looking from humans eyes, thus “putting itself to humans perspective”. In humans, the “visual perspective taking” ability begins to appear by 24 months of age and is used to determine if another person can see an object or not. In this paper, we present a geometric reasoning mechanism that employs psychological concepts of “perspective taking” and “mental rotation” in order to reason what the human sees, what the robot sees and where the robot should focus to share humans attention. This geometric reasoning mechanism is demonstrated with HRP-2 humanoid robot in a human-robot face-to-face interaction context.