Paper ID: 2310.02324

ALT-Pilot: Autonomous navigation with Language augmented Topometric maps

Mohammad Omama, Pranav Inani, Pranjal Paul, Sarat Chandra Yellapragada, Krishna Murthy Jatavallabhula, Sandeep Chinchali, Madhava Krishna

We present an autonomous navigation system that operates without assuming HD LiDAR maps of the environment. Our system, ALT-Pilot, relies only on publicly available road network information and a sparse (and noisy) set of crowdsourced language landmarks. With the help of onboard sensors and a language-augmented topometric map, ALT-Pilot autonomously pilots the vehicle to any destination on the road network. We achieve this by leveraging vision-language models pre-trained on web-scale data to identify potential landmarks in a scene, incorporating vision-language features into the recursive Bayesian state estimation stack to generate global (route) plans, and a reactive trajectory planner and controller operating in the vehicle frame. We implement and evaluate ALT-Pilot in simulation and on a real, full-scale autonomous vehicle and report improvements over state-of-the-art topometric navigation systems by a factor of 3x on localization accuracy and 5x on goal reachability

Submitted: Oct 3, 2023