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research:projects [2021/10/25 21:59]
Justus Piater
research:projects [2021/11/22 10:39] (current)
Alejandro Agostini
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 ===== Current Projects ===== ===== Current Projects =====
  
-**ELSA** - Effective Learning of Social ​Affordancesfor human-robot interaction ​(ANR/FWF AAPG, 2022-2026): Affordances are action opportunities directly perceived by an agent to interact with its environment. The concept is gaining interest in robotics, where it offers a rich description of the objects and the environment,​ focusing on the potential interactions rather than the sole physical properties. In this project, we extend this notion to social affordances. The goal is for robots to autonomously learn not only the physical effects of interactive actions with humans, but also the humansʼ reactions they produce (emotion, speech, movement). For instance, pointing and gazing in the same direction make humans orient towards the pointed direction, while pointing and looking at the finger make humans look at the finger. Besides, scratching the robotʼs chin makes some but not all humans smile. The project will investigate how learning human- general and human-specific social affordances can enrich a robotʼs action repertoire for human-aware task planning and efficient human-robot interaction.+**ELSA** - Effective Learning of Social ​Affordances for Human-Robot Interaction ​(ANR/FWF AAPG, 2022-2026): Affordances are action opportunities directly perceived by an agent to interact with its environment. The concept is gaining interest in robotics, where it offers a rich description of the objects and the environment,​ focusing on the potential interactions rather than the sole physical properties. In this project, we extend this notion to social affordances. The goal is for robots to autonomously learn not only the physical effects of interactive actions with humans, but also the humansʼ reactions they produce (emotion, speech, movement). For instance, pointing and gazing in the same direction make humans orient towards the pointed direction, while pointing and looking at the finger make humans look at the finger. Besides, scratching the robotʼs chin makes some but not all humans smile. The project will investigate how learning human- general and human-specific social affordances can enrich a robotʼs action repertoire for human-aware task planning and efficient human-robot interaction.
  
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-**SEAMLESS LEVELS OF ABSTRACTION FOR ROBOT COGNITION** - (Austrian Science Fund (FWF) - Lise Meitner Project, 2019-2021): The project seeks to develop a robotic cognitive architecture that overcomes the difficulties found when integrating different levels of abstractions (e.g. AI and robotic techniques) for task plan and execution in unstructured scenarios. The backbone of the project is a unified approach that permits searching for feasible solutions for new tasks execution at all the levels of abstractions simultaneously,​ where symbolic descriptions are no longer disentangled from the physical aspects they represent. ​+**SEAROCO** - Seamless Levels of Abstraction for Robot Cognition ​(Austrian Science Fund (FWF) - Lise Meitner Project, 2019-2023): The project seeks to develop a robotic cognitive architecture that overcomes the difficulties found when integrating different levels of abstractions (e.g. AI and robotic techniques) for task plan and execution in unstructured scenarios. The backbone of the project is a unified approach that permits searching for feasible solutions for new tasks execution at all the levels of abstractions simultaneously,​ where symbolic descriptions are no longer disentangled from the physical aspects they represent. ​
  
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-{{:​research:​pacman_logo2.png?​nolink&​110 |PaCMan}} [[http://​www.pacman-project.eu/​|PaCMan]] (EU FP7-ICT-STREP,​ 2013-2016) advances methods for object perception, representation and manipulation so that a robot is able to robustly manipulate objects even when those objects are unfamiliar, and even though the robot has unreliable perception and action. The proposal is founded on two assumptions. The first of these is that the representation of the object'​s shape in particular and of other properties in general will benefit from being compositional (or very loosely hierarchical and part based). The second is that manipulation planning and execution benefits from explicitly reasoning about uncertainty in object pose, shape etcetera; how it changes under the robot'​s actions, and the robot should plan actions that not only achieve the task, but gather information to make task achievement more reliable.+{{:​research:​pacman_logo2.png?​nolink&​110 |PaCMan}} [[http://​www.pacman-project.eu/​|PaCMan]] ​- Probabilistic and Compositional Representations for Object Manipulation ​(EU FP7-ICT-STREP,​ 2013-2016) advances methods for object perception, representation and manipulation so that a robot is able to robustly manipulate objects even when those objects are unfamiliar, and even though the robot has unreliable perception and action. The proposal is founded on two assumptions. The first of these is that the representation of the object'​s shape in particular and of other properties in general will benefit from being compositional (or very loosely hierarchical and part based). The second is that manipulation planning and execution benefits from explicitly reasoning about uncertainty in object pose, shape etcetera; how it changes under the robot'​s actions, and the robot should plan actions that not only achieve the task, but gather information to make task achievement more reliable.
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research/projects.1635191964.txt.gz · Last modified: 2021/10/25 21:59 by Justus Piater