activity
20132022
most citedRouting Unmanned Vehicles in GPS-Denied Environments

18 citations · 32 across the 10 of their papers we have counts for

collaborators

21 papers

cs.RO20222 cited

Cooperative Coverage with a Leader and a Wingmate in Communication-Constrained Environments

Sai Krishna Kanth Hari, Sivakumar Rathinam, Swaroop Darbha +1

We consider a mission framework in which two unmanned vehicles (UVs), a leader and a wingmate, are required to provide cooperative coverage of an environment while being within a s…

cs.MA20221 cited

Informed Steiner Trees: Sampling and Pruning for Multi-Goal Path Finding in High Dimensions

Nikhil Chandak, Kenny Chour, Sivakumar Rathinam +1

We interleave sampling based motion planning methods with pruning ideas from minimum spanning tree algorithms to develop a new approach for solving a Multi-Goal Path Finding (MGPF)…

math.OC2022

Optimal Geodesic Curvature Constrained Dubins' Paths on a Sphere

Swaroop Darbha, Athindra Pavan, K. R. Rajagopal +3

In this article, we consider the motion planning of a rigid object on the unit sphere with a unit speed. The motion of the object is constrained by the maximum absolute value, $U_{…

cs.RO20221 cited

LIDAR data based Segmentation and Localization using Open Street Maps for Rural Roads

Stephen Ninan, Sivakumar Rathinam

Accurate pose estimation is a fundamental ability that all mobile robots must posses in order to traverse robustly in a given environment. Much like a human, this ability is depend…

cs.AI20222 cited

Enhanced Multi-Objective A* Using Balanced Binary Search Trees

Zhongqiang Ren, Richard Zhan, Sivakumar Rathinam +2

This work addresses a Multi-Objective Shortest Path Problem (MO-SPP) on a graph where the goal is to find a set of Pareto-optimal solutions from a start node to a destination in th…

cs.AI20213 cited

Subdimensional Expansion Using Attention-Based Learning For Multi-Agent Path Finding

Lakshay Virmani, Zhongqiang Ren, Sivakumar Rathinam +1

Multi-Agent Path Finding (MAPF) finds conflict-free paths for multiple agents from their respective start to goal locations. MAPF is challenging as the joint configuration space gr…