Adam Allevato — accepted AI-conference papers

2020

Learning Labeled Robot Affordance Models Using Simulations and Crowdsourcing

Adam Allevato, Elaine Short, Mitch Pryor, Andrea Thomaz

RSS 2020poster

Affordance models are widely used in robotics to represent a robot's possible interactions with its environment. However, robot affordance models are inherently quantitative, making them difficult for humans to understand and interact with. To address this problem, previous works have constructed af…

Cited by 8 Source ↗PDF ↗code ↗Scholar ↗

2019

TuneNet: One-Shot Residual Tuning for System Identification and Sim-to-Real Robot Task Transfer

Adam Allevato, Elaine Schaertl Short, Mitch Pryor, Andrea Thomaz

CoRL 2019

As researchers teach robots to perform more and more complex tasks, the need for realistic simulation environments is growing. Existing techniques for closing the reality gap by approximating real-world physics often require extensive real world data and/or thousands of simulation samples. This pape

Cited by 0 Source ↗PDF ↗code ↗Scholar ↗