5 accepted papers
Autonomous mobile robots (AMR) operating in the real world often need to make critical decisions that directly impact their own safety and the safety of their surroundings. Learning-based approaches for decision making have gained popularity in recent years, since decisions can be made very quickly…
A majority of collision avoidance and motion planning algorithms deployed on autonomous mobile robots tend to be reactive to the presence and motion of nearby dynamic actors. While these algorithms can produce collision free navigation, they do not necessarily follow social protocol and exhibit unna
The lack of communication between agents in a multi-robot system is often regarded as a limiting factor that can affect and delay cooperative exploration and exploitation of cluttered and uncertain environments. On the contrary, this paper proposes a complete planning framework to enable cooperative…
Mobile robots are traditionally developed to be reactive and avoid collisions with surrounding humans, often moving in unnatural ways without following social protocols, forcing people to behave very differently from human-human interaction rules. Humans, on the other hand, are seamlessly able to un…
For safe and efficient human-robot interaction, a robot needs to predict and understand the intentions of humans who share the same space. Mobile robots are traditionally built to be reactive, moving in unnatural ways without following social protocol, hence forcing people to behave very differently…