activity
20182023
most citedDiffLoop: Tuning PID controllers by differentiating through the feedback loop

14 citations · 29 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SY2023

Fast, Smooth, and Safe: Implicit Control Barrier Functions through Reach-Avoid Differential Dynamic Programming

Athindran Ramesh Kumar, Kai-Chieh Hsu, Peter J. Ramadge +1

Safety is a central requirement for autonomous system operation across domains. Hamilton-Jacobi (HJ) reachability analysis can be used to construct "least-restrictive" safety filte…

cs.RO2022

Malleable Agents for Re-Configurable Robotic Manipulators

Athindran Ramesh Kumar, Gurudutt Hosangadi

Re-configurable robots have more utility and flexibility for many real-world tasks. Designing a learning agent to operate such robots requires adapting to different configurations.…

cs.LG2021★ 2 cited

ProBF: Learning Probabilistic Safety Certificates with Barrier Functions

Athindran Ramesh Kumar, Sulin Liu, Jaime F. Fisac +2

Safety-critical applications require controllers/policies that can guarantee safety with high confidence. The control barrier function is a useful tool to guarantee safety if we ha…

eess.SY2021★ 14 cited

DiffLoop: Tuning PID controllers by differentiating through the feedback loop

Athindran Ramesh Kumar, Peter J. Ramadge

Since most industrial control applications use PID controllers, PID tuning and anti-windup measures are significant problems. This paper investigates tuning the feedback gains of a…

cs.CV2018★ 13 cited

Pack and Detect: Fast Object Detection in Videos Using Region-of-Interest Packing

Athindran Ramesh Kumar, Balaraman Ravindran, Anand Raghunathan

Object detection in videos is an important task in computer vision for various applications such as object tracking, video summarization and video search. Although great progress h…