52 citations · 66 across the 11 of their papers we have counts for
6 papers · 1 filter
TerraTransfer++: Demonstration-Free End-to-End Planner
Zikang Xiong, Weixin Li, Zhouchonghao Wu +6
End-to-end autonomous driving has achieved state-of-the-art performance on benchmarks and real-world deployments. Its standard training recipe, however, is expensive across all exi…
A Framework for Learning Scoring Rules in Autonomous Driving Planning Systems
Zikang Xiong, Joe Kurian Eappen, Suresh Jagannathan
In autonomous driving systems, motion planning is commonly implemented as a two-stage process: first, a trajectory proposer generates multiple candidate trajectories, then a scorin…
SELP: Generating Safe and Efficient Task Plans for Robot Agents with Large Language Models
Yi Wu, Zikang Xiong, Yiran Hu +5
Despite significant advancements in large language models (LLMs) that enhance robot agents' understanding and execution of natural language (NL) commands, ensuring the agents adher…
Manipulating Neural Path Planners via Slight Perturbations
Zikang Xiong, Suresh Jagannathan
Data-driven neural path planners are attracting increasing interest in the robotics community. However, their neural network components typically come as black boxes, obscuring the…
Co-learning Planning and Control Policies Constrained by Differentiable Logic Specifications
Zikang Xiong, Daniel Lawson, Joe Eappen +2
Synthesizing planning and control policies in robotics is a fundamental task, further complicated by factors such as complex logic specifications and high-dimensional robot dynamic…
Model-free Neural Lyapunov Control for Safe Robot Navigation
Zikang Xiong, Joe Eappen, Ahmed H. Qureshi +1
Model-free Deep Reinforcement Learning (DRL) controllers have demonstrated promising results on various challenging non-linear control tasks. While a model-free DRL algorithm can s…