5 papers
ASHiTA: Automatic Scene-grounded HIerarchical Task Analysis
Yun Chang, Leonor Fermoselle, Duy Ta +3
While recent work in scene reconstruction and understanding has made strides in grounding natural language to physical 3D environments, it is still challenging to ground abstract,…
Zero-shot Object-Centric Instruction Following: Integrating Foundation Models with Traditional Navigation
Sonia Raychaudhuri, Duy Ta, Katrina Ashton +3
Large scale scenes such as multifloor homes can be robustly and efficiently mapped with a 3D graph of landmarks estimated jointly with robot poses in a factor graph, a technique co…
Continuously Improving Mobile Manipulation with Autonomous Real-World RL
Russell Mendonca, Emmanuel Panov, Bernadette Bucher +2
We present a fully autonomous real-world RL framework for mobile manipulation that can learn policies without extensive instrumentation or human supervision. This is enabled by 1)…
VLFM: Vision-Language Frontier Maps for Zero-Shot Semantic Navigation
Naoki Yokoyama, Sehoon Ha, Dhruv Batra +2
Understanding how humans leverage semantic knowledge to navigate unfamiliar environments and decide where to explore next is pivotal for developing robots capable of human-like sea…
EVORA: Deep Evidential Traversability Learning for Risk-Aware Off-Road Autonomy
Xiaoyi Cai, Siddharth Ancha, Lakshay Sharma +7
Traversing terrain with good traction is crucial for achieving fast off-road navigation. Instead of manually designing costs based on terrain features, existing methods learn terra…