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Found 9 papers, 0 papers with code
An Epistemic Human-Aware Task Planner which Anticipates Human Beliefs and Decisions
Our objective is to build a robot policy that accounts for uncontrollable human behaviors, thus enabling the anticipation of possible advancements achieved by the robot when the execution is not shared, e. g. when humans are briefly absent from the shared environment to complete a subtask.
Principles and Guidelines for Evaluating Social Robot Navigation Algorithms
A major challenge to deploying robots widely is navigation in human-populated environments, commonly referred to as social robot navigation.
Robust Robot Planning for Human-Robot Collaboration
Based on this, we propose two contributions: 1) an approach to automatically generate an uncertain human behavior (a policy) for each given objective function while accounting for possible robot behaviors; and 2) a robot planning algorithm that is robust to the above-mentioned uncertainties and relies on solving a partially observable Markov decision process (POMDP) obtained by reasoning on a distribution over human behaviors.
Robust Planning for Human-Robot Joint Tasks with Explicit Reasoning on Human Mental State
We consider the human-aware task planning problem where a human-robot team is given a shared task with a known objective to achieve.
Logic-Based Ethical Planning
In this paper we propose a framework for ethical decision making in the context of planning, with intended application to robotics.
MuMMER: Socially Intelligent Human-Robot Interaction in Public Spaces
In the EU-funded MuMMER project, we have developed a social robot designed to interact naturally and flexibly with users in public spaces such as a shopping mall.
Semantic Spatial Representation: a unique representation of an environment based on an ontology for robotic applications
It is important, for human-robot interaction, to endow the robot with the knowledge necessary to understand human needs and to be able to respond to them.
HATP: An HTN Planner for Robotics
Hierarchical Task Network (HTN) planning is a popular approach that cuts down on the classical planning search space by relying on a given hierarchical library of domain control knowledge.
Towards Combining HTN Planning and Geometric Task Planning
In this paper we present an interface between a symbolic planner and a geometric task planner, which is different to a standard trajectory planner in that the former is able to perform geometric reasoning on abstract entities---tasks.
