Jeel Chatrola

Worcester, MA, USA

I am a MS in Robotics Student at Worcester Polytechnic Institute. My research interests include formal control for robotics and vision based control.

Previously, I was a Research Assistant at the Formal Control and Autonomous Systems Lab (FOCAS Lab) at Center for Cyber Physical Systems (CPS), IISc Bangalore, supervised by Prof. Pushpak Jagtap.

I graduated from Pandit Deendayal Energy University in 2022, where I majored in Electrical Engineering.

Select Publications

2023

Scalable Distributed Controller Synthesis for Multi-Agent Systems Using Barrier Functions and Symbolic Control

Jeel. Chatrola, Sundarsingh. DS, Jay. Bhagiya, Adnane. Saoud, and 2 more authors

62nd Conference on Decision and Control (CDC) , Dec 2023

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In this paper, we propose a computationally efficient symbolic controller synthesis technique for multi-agent systems. The paper focuses on synthesizing distributed controllers enforcing local temporal logic specifications along with global safety specifications for multi-agent systems. To solve the problem in a computationally efficient way we leverage the concept of control barrier functions. In particular, we use a three-step bottom-up approach: first, the symbolic controllers for individual agents are synthesized to enforce local temporal logic specifications, then we use a notion of control barrier functions for symbolic models to compose controlled agent systems by removing unsafe transitions, and finally, we synthesize controller for the reduced composed system to ensure the satisfaction of local temporal logic specifications while ensuring global safety specification. The effectiveness of our approach is demonstrated on a multi-robot system by comparing it with the conventional monolithic symbolic control approach
Autonomous Exploration using Ground Robots with Safety Guarantees

Jeel. Chatrola, Sundarsingh. DS, Jay. Bhagiya, and Pushpak. Jagtap

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023), Oct 2023

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Autonomous exploration in an unknown environment is widely studied and many exploration strategies exist. However, most of the works jeopardize the safety of the robot, the environment or both. The reason behind the violation of safety by most of the exploration algorithms in real-world applications is the ignorance of the following factors (i) the dynamics and dimensions of the robot, (ii) practical constraints on states (like constrained steering angle) and inputs (like actuator saturation), and (iii) hardware constraints such as sampling time, sensor noise, modelling uncertainties, etc. In this work, we propose an autonomous exploration framework for the 2-D exploration problem that considers the factors above to provide safety guarantees for the robot and the environment. The effectiveness of this method is shown in a high-fidelity simulation of different robots with onboard sensors in different simulation environments and real-world implementation.