3 accepted papers
We present placing via picking (PvP), a method to autonomously collect real-world demonstrations for a family of placing tasks in which objects must be manipulated to specific, contact-constrained locations. With PvP, we approach the collection of robotic object placement demonstrations by reversing…
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