Creative robot tool use with large language models
Tool use is a hallmark of advanced intelligence, exemplified in both animal behavior and
robotic capabilities. This paper investigates the feasibility of imbuing robots with the ability to …
robotic capabilities. This paper investigates the feasibility of imbuing robots with the ability to …
A framework for tool cognition in robots without prior tool learning or observation
Human tool use prowess distinguishes us from other animals. In many scenarios, a human
is able to recognize objects seen for the first time as potential tools for a task and use them …
is able to recognize objects seen for the first time as potential tools for a task and use them …
ToolTango: common sense generalization in predicting sequential tool interactions for robot plan synthesis
Robots assisting us in environments such as factories or homes must learn to make use of
objects as tools to perform tasks, for instance, using a tray to carry objects. We consider the …
objects as tools to perform tasks, for instance, using a tray to carry objects. We consider the …
GOALNET: Interleaving Neural Goal Predicate Inference with Classical Planning for Generalization in Robot Instruction Following
Our goal is to enable a robot to learn how to sequence its actions to perform high-level tasks
specified as natural language instructions, given successful demonstrations from a human …
specified as natural language instructions, given successful demonstrations from a human …
Abstraction in data-sparse task transfer
When a robot adapts a learned task for a novel environment, any changes to objects in the
novel environment have an unknown effect on its task execution. For example, replacing an …
novel environment have an unknown effect on its task execution. For example, replacing an …
“Do This Instead”—Robots That Adequately Respond to Corrected Instructions
C Thierauf, R Thielstrom, B Oosterveld… - ACM Transactions on …, 2024 - dl.acm.org
Natural language instructions are effective at tasking autonomous robots and for teaching
them new knowledge quickly. Yet, human instructors are not perfect and are likely to make …
them new knowledge quickly. Yet, human instructors are not perfect and are likely to make …
Fixing symbolic plans with reinforcement learning in object-based action spaces
C Thierauf, M Scheutz - 2024 IEEE/RSJ International …, 2024 - ieeexplore.ieee.org
Reinforcement learning techniques are widely used when robots have to learn new tasks
but they typically operate on action spaces defined by the joints of the robot. We present a …
but they typically operate on action spaces defined by the joints of the robot. We present a …
Effects of Robot Competency and Motion Legibility on Human Correction Feedback
As robot deployments become more commonplace, people are likely to take on the role of
supervising robots (ie, correcting their mistakes) rather than directly teaching them. Prior …
supervising robots (ie, correcting their mistakes) rather than directly teaching them. Prior …
An approach to task representation based on object features and affordances
P Gajewski, B Indurkhya - Sensors, 2022 - mdpi.com
Multi-purpose service robots must execute their tasks reliably in different situations, as well
as learn from humans and explain their plans to them. We address these issues by …
as learn from humans and explain their plans to them. We address these issues by …
GoalNet: Inferring Conjunctive Goal Predicates from Human Plan Demonstrations for Robot Instruction Following
Our goal is to enable a robot to learn how to sequence its actions to perform tasks specified
as natural language instructions, given successful demonstrations from a human partner …
as natural language instructions, given successful demonstrations from a human partner …