4 accepted papers
This work explores the capacity of large language models (LLMs) to address problems at the intersection of spatial planning and natural language interfaces for navigation. We focus on following complex instructions that are more akin to natural conversation than traditional explicit procedural direc…
This paper introduces and develops novel touch sensing technologies that enable robots to better sense and react to to intermittent contact interactions. We present Finger-STS, a robotic finger embodiment of the See-Through-your-Skin (STS) sensor that can capture 1) an “in the hand” visual perspecti
In this paper, we present the Sample Efficient Social Navigation from Observation (SESNO) algorithm that efficiently learns socially-compliant navigation policies from observations of human trajectories. SESNO is an inverse reinforcement learning (IRL)-based algorithm that learns from human trajecto…
One of the main challenges of operating mobile robots in social environments is the safe and fluid navigation therein, specifically the ability to share a space with other human inhabitants by complying with the explicit and implicit rules that we humans follow during navigation. While these rules c