activity
20192021
most citedLearning Safe Multi-Agent Control with Decentralized Neural Barrier Certificates

48 citations · 52 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2021

Generalized Conflict-directed Search for Optimal Ordering Problems

Jingkai Chen, Yuening Zhang, Cheng Fang +1

Solving planning and scheduling problems for multiple tasks with highly coupled state and temporal constraints is notoriously challenging. An appealing approach to effectively deco…

cs.RO2021

Optimal Mixed Discrete-Continuous Planning for Linear Hybrid Systems

Jingkai Chen, Brian Williams, Chuchu Fan

Planning in hybrid systems with both discrete and continuous control variables is important for dealing with real-world applications such as extra-planetary exploration and multi-v…

cs.MA202148 cited

Learning Safe Multi-Agent Control with Decentralized Neural Barrier Certificates

Zengyi Qin, Kaiqing Zhang, Yuxiao Chen +2

We study the multi-agent safe control problem where agents should avoid collisions to static obstacles and collisions with each other while reaching their goals. Our core idea is t…

cs.RO20203 cited

Scalable and Safe Multi-Agent Motion Planning with Nonlinear Dynamics and Bounded Disturbances

Jingkai Chen, Jiaoyang Li, Chuchu Fan +1

We present a scalable and effective multi-agent safe motion planner that enables a group of agents to move to their desired locations while avoiding collisions with obstacles and o…

cs.AI20191 cited

Efficiently Exploring Ordering Problems through Conflict-directed Search

Jingkai Chen, Cheng Fang, David Wang +2

In planning and scheduling, solving problems with both state and temporal constraints is hard since these constraints may be highly coupled. Judicious orderings of events enable so…