5 papers
Learning Sampling Distribution and Safety Filter for Autonomous Driving with VQ-VAE and Differentiable Optimization
Simon Idoko, Basant Sharma, Arun Kumar Singh
Sampling trajectories from a distribution followed by ranking them based on a specified cost function is a common approach in autonomous driving. Typically, the sampling distributi…
End-to-End Learning of Behavioural Inputs for Autonomous Driving in Dense Traffic
Jatan Shrestha, Simon Idoko, Basant Sharma +1
Trajectory sampling in the Frenet(road-aligned) frame, is one of the most popular methods for motion planning of autonomous vehicles. It operates by sampling a set of behavioural i…
Hilbert Space Embedding-based Trajectory Optimization for Multi-Modal Uncertain Obstacle Trajectory Prediction
Basant Sharma, Aditya Sharma, K. Madhava Krishna +1
Safe autonomous driving critically depends on how well the ego-vehicle can predict the trajectories of neighboring vehicles. To this end, several trajectory prediction algorithms h…
PRIEST: Projection Guided Sampling-Based Optimization For Autonomous Navigation
Fatemeh Rastgar, Houman Masnavi, Basant Sharma +3
Efficient navigation in unknown and dynamic environments is crucial for expanding the application domain of mobile robots. The core challenge stems from the nonavailability of a fe…
UAP-BEV: Uncertainty Aware Planning using Bird's Eye View generated from Surround Monocular Images
Vikrant Dewangan, Basant Sharma, Tushar Choudhary +4
Autonomous driving requires accurate reasoning of the location of objects from raw sensor data. Recent end-to-end learning methods go from raw sensor data to a trajectory output vi…