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20182022
most citedScalable Differentiable Physics for Learning and Control

31 citations · 46 across the 9 of their papers we have counts for

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5 papers · 1 filter

cs.RO2022

WGICP: Differentiable Weighted GICP-Based Lidar Odometry

Sanghyun Son, Jing Liang, Ming Lin +1

We present a novel differentiable weighted generalized iterative closest point (WGICP) method applicable to general 3D point cloud data, including that from Lidar. Our method build…

cs.RO20202 cited

Multi-Agent Coverage in Urban Environments

Shivang Patel, Senthil Hariharan, Pranav Dhulipala +4

We study multi-agent coverage algorithms for autonomous monitoring and patrol in urban environments. We consider scenarios in which a team of flying agents uses downward facing cam…

cs.RO2020

Enhanced Transfer Learning for Autonomous Driving with Systematic Accident Simulation

Shivam Akhauri, Laura Zheng, Ming Lin

Simulation data can be utilized to extend real-world driving data in order to cover edge cases, such as vehicle accidents. The importance of handling edge cases can be observed in…

cs.RO20191 cited

ADAPS: Autonomous Driving Via Principled Simulations

Weizi Li, David Wolinski, Ming C. Lin

Autonomous driving has gained significant advancements in recent years. However, obtaining a robust control policy for driving remains challenging as it requires training data from…

cs.RO2019

LSwarm: Efficient Collision Avoidance for Large Swarms with Coverage Constraints in Complex Urban Scenes

Senthil Hariharan Arul, Adarsh Jagan Sathyamoorthy, Shivang Patel +4

In this paper, we address the problem of collision avoidance for a swarm of UAVs used for continuous surveillance of an urban environment. Our method, LSwarm, efficiently avoids co…