3 papers
cs.RO2026
Can Causal Models Enhance Robot Navigation? Online Causal Adaptation for Real-Robot Navigation
Zhitao Liang, Alex Mitrevski, Emmanuel Dean +1
Causality in robotics aims to produce more interpretable and flexible robot behaviours by enabling robots to predict the consequences of their actions; however, deploying causal mo…
cs.RO2026
A Causal Approach to Predicting and Improving Human Perceptions of Social Navigation Robots
Maximilian Diehl, Nathan Tsoi, Gustavo Chavez +2
As mobile robots are increasingly deployed in human environments, enabling them to predict how people perceive them is critical for socially adaptable navigation. Predicting percep…
cs.RO2024
Enabling Robots to Identify Missing Steps in Robot Tasks for Guided Learning from Demonstration
Maximilian Diehl, Tathagata Chakraborti, Karinne Ramirez-Amaro
Learning from Demonstration (LfD) systems are commonly used to teach robots new tasks by generating a set of skills from user-provided demonstrations. These skills can then be sequ…