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Found 10 papers, 2 papers with code
Interactive Continual Learning Architecture for Long-Term Personalization of Home Service Robots
Our results demonstrate the effectiveness of our architecture to allow a physical robot to continually adapt to the changes in the environment from limited data provided by the users (experimenters), and use the learned knowledge to perform object fetching tasks.
Utilization of Non-verbal Behaviour and Social Gaze in Classroom Human-Robot Interaction Communications
This abstract explores classroom Human-Robot Interaction (HRI) scenarios with an emphasis on the adaptation of human-inspired social gaze models in robot cognitive architecture to facilitate a more seamless social interaction.
Polar Collision Grids: Effective Interaction Modelling for Pedestrian Trajectory Prediction in Shared Space Using Collision Checks
Pedestrian motion in shared spaces is influenced by both the presence of vehicles and other pedestrians.
Pedestrian Trajectory Prediction in Pedestrian-Vehicle Mixed Environments: A Systematic Review
A practical pedestrian trajectory prediction algorithm for the use of AVs needs to consider the effect of the vehicle's interactions with the pedestrians on pedestrians' future motion behaviours.
How Do Human Users Teach a Continual Learning Robot in Repeated Interactions?
Continual learning (CL) has emerged as an important avenue of research in recent years, at the intersection of Machine Learning (ML) and Human-Robot Interaction (HRI), to allow robots to continually learn in their environments over long-term interactions with humans.
A Personalized Household Assistive Robot that Learns and Creates New Breakfast Options through Human-Robot Interaction
In this paper, we present a cognitive architecture for a household assistive robot that can learn personalized breakfast options from its users and then use the learned knowledge to set up a table for breakfast.
Continual Learning through Human-Robot Interaction -- Human Perceptions of a Continual Learning Robot in Repeated Interactions
Our results suggest that participants' perceptions of trust, competence, and usability of a continual learning robot significantly decrease over multiple sessions if the robot forgets previously learned objects.
Don't Forget to Buy Milk: Contextually Aware Grocery Reminder Household Robot
The robot can also use the learned knowledge to correctly predict missing items over multiple weeks and it is robust against sensory and perceptual errors.
Autonomous Vehicle Visual Signals for Pedestrians: Experiments and Design Recommendations
Based on the results, we distill twelve practical design recommendations for AV visual signals, with focus on signal pattern design and placement.
Human Perception of Intrinsically Motivated Autonomy in Human-Robot Interaction
A challenge in using robots in human-inhabited environments is to design behavior that is engaging, yet robust to the perturbations induced by human interaction.
