63 citations · 147 across the 32 of their papers we have counts for
7 papers · 1 filter
GPT-4V Takes the Wheel: Promises and Challenges for Pedestrian Behavior Prediction
Jia Huang, Peng Jiang, Alvika Gautam +1
Predicting pedestrian behavior is the key to ensure safety and reliability of autonomous vehicles. While deep learning methods have been promising by learning from annotated video…
Radar-Only Off-Road Local Navigation
Timothy Overbye, Srikanth Saripalli
Off-road robotics have traditionally utilized lidar for local navigation due to its accuracy and high resolution. However, the limitations of lidar, such as reduced performance in…
ROSS: Radar Off-road Semantic Segmentation
Peng Jiang, Srikanth Saripalli
As the demand for autonomous navigation in off-road environments increases, the need for effective solutions to understand these surroundings becomes essential. In this study, we c…
Online Multi-IMU Calibration Using Visual-Inertial Odometry
Jacob Hartzer, Srikanth Saripalli
This work presents a centralized multi-IMU filter framework with online intrinsic and extrinsic calibration for unsynchronized inertial measurement units that is robust against cha…
WiDEVIEW: An UltraWideBand and Vision Dataset for Deciphering Pedestrian-Vehicle Interactions
Jia Huang, Alvika Gautam, Junghun Choi +1
Robust and accurate tracking and localization of road users like pedestrians and cyclists is crucial to ensure safe and effective navigation of Autonomous Vehicles (AVs), particula…
Learning Pedestrian Actions to Ensure Safe Autonomous Driving
Jia Huang, Alvika Gautam, Srikanth Saripalli
To ensure safe autonomous driving in urban environments with complex vehicle-pedestrian interactions, it is critical for Autonomous Vehicles (AVs) to have the ability to predict pe…