The cultural origins of human cognition

https://hal.archives-ouvertes.fr/hal-01684295/document

Human-aware robot navigation: A survey

A key requirement for seamless human-robot collaboration is for the robot to make its intentions clear to its human collaborator. A collaborative robot's motion must be legible, or intent-expressive. Legibility is often described in the literature as and effect of predictable, unsurprising, or expected motion. Our central insight is that predictability and legibility are fundamentally different and often contradictory properties of motion. We develop a formalism to mathematically define and distinguish predictability and legibility of motion. We formalize the two based on inferences between trajectories and goals in opposing directions, drawing the analogy to action interpretation in psychology. We then propose mathematical models for these inferences based on optimizing cost, drawing the analogy to the principle of rational action. Our experiments validate our formalism's prediction that predictability and legibility can contradict, and provide support for our models. Our findings indicate that for robots to seamlessly collaborate with humans, they must change the way they plan their motion.

/pdf/legibility-and-predictability-of-robot-motion-4ofd3ikgsc.pdf

Legibility and predictability of robot motion

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.

/pdf/a-human-aware-mobile-robot-motion-planner-1miap4wyrt.pdf

A Human Aware Mobile Robot Motion Planner

Robot assistants and professional coworkers are becoming a commodity in domestic and industrial settings. In order to enable robots to share their workspace with humans and physically interact with them, fast and reliable handling of possible collisions on the entire robot structure is needed, along with control strategies for safe robot reaction. The primary motivation is the prevention or limitation of possible human injury due to physical contacts. In this survey paper, based on our early work on the subject, we review, extend, compare, and evaluate experimentally model-based algorithms for real-time collision detection, isolation, and identification that use only proprioceptive sensors. This covers the context-independent phases of the collision event pipeline for robots interacting with the environment, as in physical human–robot interaction or manipulation tasks. The problem is addressed for rigid robots first and then extended to the presence of joint/transmission flexibility. The basic physically motivated solution has already been applied to numerous robotic systems worldwide, ranging from manipulators and humanoids to flying robots, and even to commercial products.

/pdf/robot-collisions-a-survey-on-detection-isolation-and-vhl8g5nyiu.pdf

Robot Collisions: A Survey on Detection, Isolation, and Identification

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 human's 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.

A Human-Aware Manipulation Planner

With robotics hardware becoming more and more safe and compliant, robots are not far from entering our homes. The robot, that will share the same environment with humans, will be expected to consider the geometry of the interaction and to perform intelligent space sharing.

Synthesizing Robot Motions Adapted to Human Presence A Planning and Control Framework for Safe and Socially Acceptable Robot Motions

This paper presents the results from a Human-Robot Interaction study that investigates the issues of participants’ preferences in terms of the robot approach direction (directionRAD), robot base approach interaction distance (distanceRBAID), robot handing over hand distance (distanceRHOHD), robot handing over arm gesture (gestureRHOAG), and the coordination of both the robot approaching and gestureRHOAG in the context of a robot handing over an object to a seated person. The results from this study aim at informing the development of a Human Aware Manipulation Planner. Twelve participants with some previous human-robot interaction experience were recruited for the trial. The results show that a majority of the participants prefer the robot to approach from the front and hand them a can of soft drink in the front sector of their personal zone. The robot handing over hand position had the most influence on determining from where the robot should approach (i.e distanceRAD). Legibility and perception of risk seem to be the deciding factor on how participants choose their preferred robot arm-base approach coordination for handing over a can. Detailed discussions of the results conclude the paper.

/pdf/exploratory-study-of-a-robot-approaching-a-person-in-the-cc873dyiti.pdf

Exploratory Study of a Robot Approaching a Person in the Context of Handing Over an Object.

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

/pdf/navigation-in-the-presence-of-humans-t70a970dgh.pdf

Emrah Akin Sisbot

Papers

A Human Aware Mobile Robot Motion Planner

A Human-Aware Manipulation Planner

Synthesizing Robot Motions Adapted to Human Presence A Planning and Control Framework for Safe and Socially Acceptable Robot Motions

Exploratory Study of a Robot Approaching a Person in the Context of Handing Over an Object.

Navigation in the presence of humans