activity
20192024
most citedMulti-Agent Coverage in Urban Environments

2 citations · 3 across the 5 of their papers we have counts for

collaborators

7 papers

cs.RO20241 cited

BehAV: Behavioral Rule Guided Autonomy Using VLMs for Robot Navigation in Outdoor Scenes

Kasun Weerakoon, Mohamed Elnoor, Gershom Seneviratne +5

We present BehAV, a novel approach for autonomous robot navigation in outdoor scenes guided by human instructions and leveraging Vision Language Models (VLMs). Our method interpret…

cs.RO2022

Dense Multi-Agent Navigation Using Voronoi Cells and Congestion Metric-based Replanning

Senthil Hariharan Arul, Dinesh Manocha

We present a decentralized path-planning algorithm for navigating multiple differential-drive robots in dense environments. In contrast to prior decentralized methods, we propose a…

cs.RO2021

V-RVO: Decentralized Multi-Agent Collision Avoidance using Voronoi Diagrams and Reciprocal Velocity Obstacles

Senthil Hariharan Arul, Dinesh Manocha

We present a decentralized collision avoidance method for dense environments that is based on buffered Voronoi cells (BVC) and reciprocal velocity obstacles (RVO). Our approach is…

cs.RO2020

SwarmCCO: Probabilistic Reactive Collision Avoidance for Quadrotor Swarms under Uncertainty

Senthil Hariharan Arul, Dinesh Manocha

We present decentralized collision avoidance algorithms for quadrotor swarms operating under uncertain state estimation. Our approach exploits the differential flatness property an…

cs.RO20202 cited

Multi-Agent Coverage in Urban Environments

Shivang Patel, Senthil Hariharan, Pranav Dhulipala +4

We study multi-agent coverage algorithms for autonomous monitoring and patrol in urban environments. We consider scenarios in which a team of flying agents uses downward facing cam…

cs.RO2019

DCAD: Decentralized Collision Avoidance with Dynamics Constraints for Agile Quadrotor Swarms

Senthil Hariharan Arul, Dinesh Manocha

We present a novel, decentralized collision avoidance algorithm for navigating a swarm of quadrotors in dense environments populated with static and dynamic obstacles. Our algorith…