4 accepted papers
Robot navigation in human spaces today largely relies on the construction of precise geometric maps and a global motion plan. In this work, we navigate with only local sensing by using available signage - as designed for humans - in human-made environments such as airports. We propose a formalizatio…
We propose a joint simulation and real-world learning framework for mapping navigation instructions and raw first-person observations to continuous control. Our model estimates the need for environment exploration, predicts the likelihood of visiting environment positions during execution, and contr
We propose an approach for mapping natural language instructions and raw observations to continuous control of a quadcopter drone. Our model predicts interpretable position-visitation distributions indicating where the agent should go during execution and where it should stop, and uses the predicted
We present a novel, data-driven framework for planning socially competent robot behaviors in crowded environments. The core of our approach is a topological model of collective navigation behaviors, based on braid groups. This model constitutes the basis for the design of a human-inspired probabilis…