6 papers · 1 filter
KGLAMP: Knowledge Graph-guided Language model for Adaptive Multi-robot Planning and Replanning
Chak Lam Shek, Faizan M. Tariq, Sangjae Bae +2
Heterogeneous multi-robot systems are increasingly used in long-horizon missions requiring coordinated planning across diverse capabilities. However, existing planning approaches s…
Contextual Neural Moving Horizon Estimation for Robust Quadrotor Control in Varying Conditions
Kasra Torshizi, Chak Lam Shek, Khuzema Habib +3
Adaptive controllers on quadrotors typically rely on estimation of disturbances to ensure robust trajectory tracking. Estimating disturbances across diverse environmental contexts…
Learning Multi-Robot Coordination through Locality-Based Factorized Multi-Agent Actor-Critic Algorithm
Chak Lam Shek, Amrit Singh Bedi, Anjon Basak +5
In this work, we present a novel cooperative multi-agent reinforcement learning method called \textbf{Loc}ality based \textbf{Fac}torized \textbf{M}ulti-Agent \textbf{A}ctor-\textb…
When to Localize? A Risk-Constrained Reinforcement Learning Approach
Chak Lam Shek, Kasra Torshizi, Troi Williams +1
In a standard navigation pipeline, a robot localizes at every time step to lower navigational errors. However, in some scenarios, a robot needs to selectively localize when it is e…
LANCAR: Leveraging Language for Context-Aware Robot Locomotion in Unstructured Environments
Chak Lam Shek, Xiyang Wu, Wesley A. Suttle +5
Navigating robots through unstructured terrains is challenging, primarily due to the dynamic environmental changes. While humans adeptly navigate such terrains by using context fro…
Where to Drop Sensors from Aerial Robots to Monitor a Surface-Level Phenomenon?
Chak Lam Shek, Guangyao Shi, Ahmad Bilal Asghar +1
We consider the problem of routing a team of energy-constrained Unmanned Aerial Vehicles (UAVs) to drop unmovable sensors for monitoring a task area in the presence of stochastic w…