
Multi-Agent Warehouse Coverage & Cleaning
Efficient coverage and cleaning of unknown terrains using multiple ground robots.
Detecting and Mitigating System-Level Anomalies of Vision-Based Controllers
Aryaman Gupta, Kaustav Chakraborty, Somil Bansal
IEEE International Conference on Robotics and Automation (ICRA), 2024
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[Website]
[Video]
[Code]
Enhancing Safety and Robustness of Vision-Based Controllers via Reachability Analysis
Kaustav Chakraborty, Aryaman Gupta, Somil Bansal
arXiv, 2024
[PDF]
[Website]
[Video]
Deep Reinforcement Learning for Sim-to-Real Policy Transfer of VTOL-UAVs Offshore Docking Operations
Ali Mohamed Ali, Aryaman Gupta, Hashim A. Hashim
Applied Soft Computing Journal
[PDF]
[Website]
[Code]
Node Fault Prediction Assisted Small-World IoT Networks Using ML Frameworks: Towards Performance Improvement
Neha Sharma, Aryaman Gupta, Sivala Deepak, Om Jee Pandey [Best Paper Award]
IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), 2024
[PDF]
[Website]
[Code]
Doctor of Philosophy (Ph.D.) | Aeronautics and Astronautics | January 2025 - Present
Working with Prof. Somil Bansal at SIA Lab on performing runtime safety monitoring for output-feedback policies in autonomous systems.
Bachelor of Technology (B.Tech.) | Electronics Engineering | November 2020 - May 2024
Completed bachelor thesis under Prof. Om Jee Pandey on efficient data routing in optimal small-world wireless sensor networks using deep-RL.
Research Intern | Prof. Somil Bansal | May 2023 - August 2024
Worked on mitigating system-level failures of vision-based controllers in aircraft taxiing and ground robot navigation tasks using reachability analysis.
Research Intern | Dr. Hashim Mohamed | Jan 2023 - Dec 2023
Worked on developing a deep-RL based docking mechanism for VTOL UAVs on offshore platforms.
Research Intern | Dr. Bharadwaj Amrutur | May 2022 - July 2022
Worked on multi-agent exploration using RRT-based methods and dynamic obstacle avoidance using 3D object detection.
Research Intern | Dr. Oh-Seol Kwon | Mar 2022 - July 2022
Worked on combining Faster R-CNN and Edge Enhanced SRGAN architectures for enhanced object detection in low resolution aerial images.
Efficient coverage and cleaning of unknown terrains using multiple ground robots.
RRT-Exploration and visual obstacle detection and avoidance package.
Cascaded PID-based control and swarm motion of drones.
Fabricated a ground robot to perform household chores and child care.
Enhanced network performance by introducing small-world phenomenon using actor-critic reinforcement learning.
UAV aided mapping and localization for a UGV to autonomously traverse in mountainous terrains.