1 citations · 2 across the 6 of their papers we have counts for
7 papers
Generalizable Multi-Agent Planning from Signal Temporal Logic Specifications via Diffusion
Joe Eappen, Zikang Xiong, Shreyash S. Iyengar +1
Multi-agent systems in the real-world (e.g., drone swarms, autonomous cars, warehouse robots) must satisfy rich, temporal tasks while avoiding collisions. Signal Temporal Logic (ST…
Graph-of-Constraints Model Predictive Control for Reactive Multi-agent Task and Motion Planning
Anastasios Manganaris, Jeremy Lu, Ahmed H. Qureshi +1
Sequences of interdependent geometric constraints are central to many multi-agent Task and Motion Planning (TAMP) problems. However, existing methods for handling such constraint s…
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…
Scaling Safe Multi-Agent Control for Signal Temporal Logic Specifications
Joe Eappen, Zikang Xiong, Dipam Patel +2
Existing methods for safe multi-agent control using logic specifications like Signal Temporal Logic (STL) often face scalability issues. This is because they rely either on single-…
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…