4 citations · 6 across the 3 of their papers we have counts for
6 papers
Moral-Trust Violation vs Performance-Trust Violation by a Robot: Which Hurts More?
Zahra Rezaei Khavas, Russell Perkins, S. Reza Ahmadzadeh +1
In recent years a modern conceptualization of trust in human-robot interaction (HRI) was introduced by Ullman et al.\cite{ullman2018does}. This new conceptualization of trust sugge…
Towards Mobile Multi-Task Manipulation in a Confined and Integrated Environment with Irregular Objects
Zhao Han, Jordan Allspaw, Gregory LeMasurier +4
The FetchIt! Mobile Manipulation Challenge, held at the IEEE International Conference on Robots and Automation (ICRA) in May 2019, offered an environment with complex and integrate…
Benchmark for Skill Learning from Demonstration: Impact of User Experience, Task Complexity, and Start Configuration on Performance
M. Asif Rana, Daphne Chen, S. Reza Ahmadzadeh +3
In this work, we contribute a large-scale study benchmarking the performance of multiple motion-based learning from demonstration approaches. Given the number and diversity of exis…
Skill Acquisition via Automated Multi-Coordinate Cost Balancing
Harish Ravichandar, S. Reza Ahmadzadeh, M. Asif Rana +1
We propose a learning framework, named Multi-Coordinate Cost Balancing (MCCB), to address the problem of acquiring point-to-point movement skills from demonstrations. MCCB encodes…
Learning Generalizable Robot Skills from Demonstrations in Cluttered Environments
Muhammad Asif Rana, Mustafa Mukadam, Seyed Reza Ahmadzadeh +2
Learning from Demonstration (LfD) is a popular approach to endowing robots with skills without having to program them by hand. Typically, LfD relies on human demonstrations in clut…
Visuospatial Skill Learning for Robots
S. Reza Ahmadzadeh, Fulvio Mastrogiovanni, Petar Kormushev
A novel skill learning approach is proposed that allows a robot to acquire human-like visuospatial skills for object manipulation tasks. Visuospatial skills are attained by observi…