3 citations · 6 across the 6 of their papers we have counts for
7 papers
Quad-LCD: Layered Control Decomposition Enables Actuator-Feasible Quadrotor Trajectory Planning
Anusha Srikanthan, Hanli Zhang, Spencer Folk +2
In this work, we specialize contributions from prior work on data-driven trajectory generation for a quadrotor system with motor saturation constraints. When motors saturate in qua…
ADMM-MCBF-LCA: A Layered Control Architecture for Safe Real-Time Navigation
Anusha Srikanthan, Yifan Xue, Vijay Kumar +2
We consider the problem of safe real-time navigation of a robot in a dynamic environment with moving obstacles of arbitrary smooth geometries and input saturation constraints. We a…
Closed-loop Analysis of ADMM-based Suboptimal Linear Model Predictive Control
Anusha Srikanthan, Aren Karapetyan, Vijay Kumar +1
Many practical applications of optimal control are subject to real-time computational constraints. When applying model predictive control (MPC) in these settings, respecting timing…
Why Change Your Controller When You Can Change Your Planner: Drag-Aware Trajectory Generation for Quadrotor Systems
Hanli Zhang, Anusha Srikanthan, Spencer Folk +2
Motivated by the increasing use of quadrotors for payload delivery, we consider a joint trajectory generation and feedback control design problem for a quadrotor experiencing aerod…
Augmented Lagrangian Methods as Layered Control Architectures
Anusha Srikanthan, Vijay Kumar, Nikolai Matni
For optimal control problems that involve planning and following a trajectory, two degree of freedom (2DOF) controllers are a ubiquitously used control architecture that decomposes…
A Data-Driven Approach to Synthesizing Dynamics-Aware Trajectories for Underactuated Robotic Systems
Anusha Srikanthan, Fengjun Yang, Igor Spasojevic +3
We consider joint trajectory generation and tracking control for under-actuated robotic systems. A common solution is to use a layered control architecture, where the top layer use…