48 citations · 155 across the 22 of their papers we have counts for
22 papers
That was not what I was aiming at! Differentiating human intent and outcome in a physically dynamic throwing task
Vidullan Surendran, Alan R. Wagner
Recognising intent in collaborative human robot tasks can improve team performance and human perception of robots. Intent can differ from the observed outcome in the presence of mi…
CBCL-PR: A Cognitively Inspired Model for Class-Incremental Learning in Robotics
Ali Ayub, Alan R. Wagner
For most real-world applications, robots need to adapt and learn continually with limited data in their environments. In this paper, we consider the problem of Few-Shot class Incre…
Learning Evacuee Models from Robot-Guided Emergency Evacuation Experiments
Mollik Nayyar, Ghanghoon Paik, Zhenyuan Yuan +4
Recent research has examined the possibility of using robots to guide evacuees to safe exits during emergencies. Yet, there are many factors that can impact a person's decision to…
Multi-Robot-Guided Crowd Evacuation: Two-Scale Modeling and Control
Tongjia Zheng, Zhenyuan Yuan, Mollik Nayyar +3
Emergency evacuation describes a complex situation involving time-critical decision-making by evacuees. Mobile robots are being actively explored as a potential solution to provide…
Using Virtual Reality to Simulate Human-Robot Emergency Evacuation Scenarios
Alan R. Wagner, Colin Holbrook, Daniel Holman +5
This paper describes our recent effort to use virtual reality to simulate threatening emergency evacuation scenarios in which a robot guides a person to an exit. Our prior work has…
Multi-Robot-Assisted Human Crowd Evacuation using Navigation Velocity Fields
Tongjia Zheng, Zhenyuan Yuan, Mollik Nayyar +3
This work studies a robot-assisted crowd evacuation problem where we control a small group of robots to guide a large human crowd to safe locations. The challenge lies in how to mo…
Toward Ethical Robotic Behavior in Human-Robot Interaction Scenarios
Shengkang Chen, Vidullan Surendran, Alan R. Wagner +2
This paper describes current progress on developing an ethical architecture for robots that are designed to follow human ethical decision-making processes. We surveyed both regular…
If you Cheat, I Cheat: Cheating on a Collaborative Task with a Social Robot
Ali Ayub, Huiqing Hu, Guangwei Zhou +4
Robots may soon play a role in higher education by augmenting learning environments and managing interactions between instructors and learners. Little, however, is known about how…
Don't Get Yourself into Trouble! Risk-aware Decision-Making for Autonomous Vehicles
Kasra Mokhtari, Alan R. Wagner
Risk is traditionally described as the expected likelihood of an undesirable outcome, such as collisions for autonomous vehicles. Accurately predicting risk or potentially risky si…
Safe Deep Q-Network for Autonomous Vehicles at Unsignalized Intersection
Kasra Mokhtari, Alan R. Wagner
We propose a safe DRL approach for autonomous vehicle (AV) navigation through crowds of pedestrians while making a left turn at an unsignalized intersection. Our method uses two lo…
Pedestrian Collision Avoidance for Autonomous Vehicles at Unsignalized Intersection Using Deep Q-Network
Kasra Mokhtari, Alan R. Wagner
Prior research has extensively explored Autonomous Vehicle (AV) navigation in the presence of other vehicles, however, navigation among pedestrians, who are the most vulnerable ele…
F-SIOL-310: A Robotic Dataset and Benchmark for Few-Shot Incremental Object Learning
Ali Ayub, Alan R. Wagner
Deep learning has achieved remarkable success in object recognition tasks through the availability of large scale datasets like ImageNet. However, deep learning systems suffer from…
Learning Novel Objects Continually Through Curiosity
Ali Ayub, Alan R. Wagner
Children learn continually by asking questions about the concepts they are most curious about. With robots becoming an integral part of our society, they must also learn unknown co…
Continual Learning of Visual Concepts for Robots through Limited Supervision
Ali Ayub, Alan R. Wagner
For many real-world robotics applications, robots need to continually adapt and learn new concepts. Further, robots need to learn through limited data because of scarcity of labele…
EEC: Learning to Encode and Regenerate Images for Continual Learning
Ali Ayub, Alan R. Wagner
The two main impediments to continual learning are catastrophic forgetting and memory limitations on the storage of data. To cope with these challenges, we propose a novel, cogniti…
What am I allowed to do here?: Online Learning of Context-Specific Norms by Pepper
Ali Ayub, Alan R. Wagner
Social norms support coordination and cooperation in society. With social robots becoming increasingly involved in our society, they also need to follow the social norms of the soc…
Tell me what this is: Few-Shot Incremental Object Learning by a Robot
Ali Ayub, Alan R. Wagner
For many applications, robots will need to be incrementally trained to recognize the specific objects needed for an application. This paper presents a practical system for incremen…
Storing Encoded Episodes as Concepts for Continual Learning
Ali Ayub, Alan R. Wagner
The two main challenges faced by continual learning approaches are catastrophic forgetting and memory limitations on the storage of data. To cope with these challenges, we propose…
Cognitively-Inspired Model for Incremental Learning Using a Few Examples
Ali Ayub, Alan Wagner
Incremental learning attempts to develop a classifier which learns continuously from a stream of data segregated into different classes. Deep learning approaches suffer from catast…
The Pedestrian Patterns Dataset
Kasra Mokhtari, Alan R. Wagner
We present the pedestrian patterns dataset for autonomous driving. The dataset was collected by repeatedly traversing the same three routes for one week starting at different speci…
Teach Me What You Want to Play: Learning Variants of Connect Four through Human-Robot Interaction
Ali Ayub, Alan R. Wagner
This paper investigates the use of game theoretic representations to represent and learn how to play interactive games such as Connect Four. We combine aspects of learning by demon…
Centroid Based Concept Learning for RGB-D Indoor Scene Classification
Ali Ayub, Alan R. Wagner
This paper contributes a novel cognitively-inspired method for RGB-D indoor scene classification. High intra-class variance and low inter-class variance make indoor scene classific…