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Sivakumar Rathinam

Also published under: S. Rathinam, Siva Rathinam

Publications
71
Citations
1,353
Publications by Year
20042025
Co-Authors:
Show All Co-Authors (86)
Image of author Sivakumar Rathinam

Sivakumar Rathinam

Also published under: S. Rathinam, Siva Rathinam

Affiliation

Department of Mechanical Engineering and Department of Computer Science and Engineering
Texas A&M University
College Station, TX, USA

Publication Topics

Biography

Sivakumar Rathinam is currently a graduate student in the Systems program at the University of California, Berkeley. His research interests include optimization, control and mechanics. He obtained his B. Tech. degree in mechanical engineering from indian Institute of Technology-Madras, India in 1999 and M.S. degree in mechanical engineering from Texas A & M University, College Station in2001.(Based on document published on 20 December 2004).
Publications
71
Citations
1,353
Publications by Year
20042025
Co-Authors:
Show All Co-Authors (86)
Author's Published Works

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Heuristic Search for Path Finding With Refuelling

Shizhe Zhao;Anushtup Nandy;Howie Choset;Sivakumar Rathinam;Zhongqiang Ren

IEEE Robotics and Automation Letters
Year: 2025 | Volume: 10, Issue: 4 | Journal Article |
This letter considers a generalization of the Path Finding (PF) problem with refuelling constraints referred to as the Gas Station Problem (GSP). Similar to PF, given a graph where vertices are gas stations with known fuel prices, and edge costs are the gas consumption between the two vertices, GSPseeks a minimum-cost path from the start to the goal vertex for a robot with a limited gas tank and a...Show More

Heuristic Search for Path Finding With Refuelling

Shizhe Zhao;Anushtup Nandy;Howie Choset;Sivakumar Rathinam;Zhongqiang Ren

Year: 2025 | Volume: 10, Issue: 4 | Journal Article |

The Persistent Robot Charging Problem for Long-Duration Autonomy

Nitesh Kumar;Jaekyung Jackie Lee;Sivakumar Rathinam;Swaroop Darbha;P. B. Sujit;Rajiv Raman

IEEE Robotics and Automation Letters
Year: 2025 | Volume: 10, Issue: 3 | Journal Article |
This paper introduces a novel formulation for finding the recharging schedule for a fleet of n heterogeneous robots that minimizes utilization of recharging resources. This study provides a foundational framework applicable to Multi-Robot Mission Planning, particularly in scenarios demanding Long-Duration Autonomy (LDA) or other contexts that necessitate periodic recharging of multiple robots. A...Show More

The Persistent Robot Charging Problem for Long-Duration Autonomy

Nitesh Kumar;Jaekyung Jackie Lee;Sivakumar Rathinam;Swaroop Darbha;P. B. Sujit;Rajiv Raman

Year: 2025 | Volume: 10, Issue: 3 | Journal Article |

A Bounded Sub-Optimal Approach for Multi-Agent Combinatorial Path Finding

Zhongqiang Ren;Sivakumar Rathinam;Howie Choset

IEEE Transactions on Automation Science and Engineering
Year: 2025 | Volume: 22 | Journal Article |
Multi-Agent Path Finding (MAPF) seeks collision-free paths for multiple agents from start to goal locations. This paper considers a generalization of MAPF called Multi-Agent Combinatorial Path Finding (MCPF) where agents must collectively visit a set of intermediate target locations before reaching their goals. MCPF is challenging as it involves both planning collision-free paths for multiple agen...Show More

A Bounded Sub-Optimal Approach for Multi-Agent Combinatorial Path Finding

Zhongqiang Ren;Sivakumar Rathinam;Howie Choset

Year: 2025 | Volume: 22 | Journal Article |

A Mixed-Integer Conic Program for the Moving-Target Traveling Salesman Problem based on a Graph of Convex Sets

Allen George Philip;Zhongqiang Ren;Sivakumar Rathinam;Howie Choset

2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Year: 2024 | Conference Paper |
This paper introduces a new formulation that finds the optimum for the Moving-Target Traveling Salesman Problem (MT-TSP), which seeks to find a shortest path for an agent, that starts at a depot, visits a set of moving targets exactly once within their assigned time-windows, and returns to the depot. The formulation relies on the key idea that when the targets move along lines, their trajectories ...Show More

A Mixed-Integer Conic Program for the Moving-Target Traveling Salesman Problem based on a Graph of Convex Sets

Allen George Philip;Zhongqiang Ren;Sivakumar Rathinam;Howie Choset

Year: 2024 | Conference Paper |

DMS*: Towards Minimizing Makespan for Multi-Agent Combinatorial Path Finding

Zhongqiang Ren;Anushtup Nandy;Sivakumar Rathinam;Howie Choset

IEEE Robotics and Automation Letters
Year: 2024 | Volume: 9, Issue: 9 | Journal Article |
Multi-Agent Combinatorial Path Finding (MCPF) seeks collision-free paths for multiple agents from their start to goal locations, while visiting a set of intermediate target locations in the middle of the paths. MCPF is challenging as it involves both planning collision-free paths for multiple agents and target sequencing, i.e., solving traveling salesman problems to assign targets to and find the ...Show More

DMS*: Towards Minimizing Makespan for Multi-Agent Combinatorial Path Finding

Zhongqiang Ren;Anushtup Nandy;Sivakumar Rathinam;Howie Choset

Year: 2024 | Volume: 9, Issue: 9 | Journal Article |

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

Nikhil Chandak;Kenny Chour;Sivakumar Rathinam;R. Ravi

IEEE Transactions on Automation Science and Engineering
Year: 2024 | Volume: 21, Issue: 4 | Journal Article |
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) problem in high dimensional spaces. The approach alternates between sampling points from selected regions in the search space and de-emphasizing regions that may not lead to good solutions for MGPF. Our approach provide...Show More

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

Nikhil Chandak;Kenny Chour;Sivakumar Rathinam;R. Ravi

Year: 2024 | Volume: 21, Issue: 4 | Journal Article |

Optimal Path Planning for a Convoy-Support Vehicle Pair Through a Repairable Network

Abhay Singh Bhadoriya;Christopher M. Montez;Sivakumar Rathinam;Swaroop Darbha;David W. Casbeer;Satyanarayana G. Manyam

IEEE Transactions on Automation Science and Engineering
Year: 2024 | Volume: 21, Issue: 4 | Journal Article |
Cited by: Papers (1)
In this article, we consider a multi-agent path planning problem in a partially impeded environment. The impeded environment is represented by a graph with select road segments (edges) in disrepair impeding vehicular movement in the road network. A primary vehicle, which we refer to as a convoy, wishes to travel from a starting location to a destination while minimizing some accumulated cost. The ...Show More

Optimal Path Planning for a Convoy-Support Vehicle Pair Through a Repairable Network

Abhay Singh Bhadoriya;Christopher M. Montez;Sivakumar Rathinam;Swaroop Darbha;David W. Casbeer;Satyanarayana G. Manyam

Year: 2024 | Volume: 21, Issue: 4 | Journal Article |

R2D2: Rural Road Detection Dataset

Stephen Ninan;Sivakumar Rathinam;Harsh Mittal;Benjamin Sunny

2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Multimodal sensor datasets play a crucial role in training machine learning algorithms for autonomous vehicles. While several such datasets exist, almost all of them deal with roads in urban settings. In this paper, we present Rural Road Detection Dataset (R2D2), a comprehensive collection of labeled point clouds for object detection and semantic segmentation of rural roads that aims to address th...Show More

R2D2: Rural Road Detection Dataset

Stephen Ninan;Sivakumar Rathinam;Harsh Mittal;Benjamin Sunny

Year: 2023 | Conference Paper |

ERCA*: A New Approach for the Resource Constrained Shortest Path Problem

Zhongqiang Ren;Zachary B. Rubinstein;Stephen F. Smith;Sivakumar Rathinam;Howie Choset

IEEE Transactions on Intelligent Transportation Systems
Year: 2023 | Volume: 24, Issue: 12 | Journal Article |
Cited by: Papers (2)
The Resource Constrained Shortest Path Problem (RCSPP) seeks to determine a minimum-cost path between a start and a goal location while ensuring that one or multiple types of resource consumed along the path do not exceed their limits. This problem is often solved on a graph where a path is incrementally built from the start towards the goal during the search. RCSPP is computationally challenging ...Show More

ERCA*: A New Approach for the Resource Constrained Shortest Path Problem

Zhongqiang Ren;Zachary B. Rubinstein;Stephen F. Smith;Sivakumar Rathinam;Howie Choset

Year: 2023 | Volume: 24, Issue: 12 | Journal Article |

Search Algorithms for Multi-Agent Teamwise Cooperative Path Finding

Zhongqiang Ren;Chaoran Zhang;Sivakumar Rathinam;Howie Choset

2023 IEEE International Conference on Robotics and Automation (ICRA)
Year: 2023 | Conference Paper |
Cited by: Papers (2)
Multi-Agent Path Finding (MA-PF) computes a set of collision-free paths for multiple agents from their respective starting locations to destinations. This paper considers a generalization of MA-PF called Multi-Agent Teamwise Cooperative Path Finding (MA-TC-PF), where agents are grouped as multiple teams and each team has its own objective to be minimized. For example, an objective can be the sum o...Show More

Search Algorithms for Multi-Agent Teamwise Cooperative Path Finding

Zhongqiang Ren;Chaoran Zhang;Sivakumar Rathinam;Howie Choset

Year: 2023 | Conference Paper |

CBSS: A New Approach for Multiagent Combinatorial Path Finding

Zhongqiang Ren;Sivakumar Rathinam;Howie Choset

IEEE Transactions on Robotics
Year: 2023 | Volume: 39, Issue: 4 | Journal Article |
Cited by: Papers (10)
Conventional multiagent path finding (MAPF) problems aim to compute an ensemble of collision-free paths for multiple agents from their respective starting locations to preallocated destinations. This article considers a generalized version of MAPF called multiagent combinatorial path finding, where agents must collectively visit a large number of intermediate target locations along their paths bef...Show More

CBSS: A New Approach for Multiagent Combinatorial Path Finding

Zhongqiang Ren;Sivakumar Rathinam;Howie Choset

Year: 2023 | Volume: 39, Issue: 4 | Journal Article |

Bounds on Optimal Revisit Times in Persistent Monitoring Missions With a Distinct and Remote Service Station

Sai Krishna Kanth Hari;Sivakumar Rathinam;Swaroop Darbha;Satyanarayana Gupta Manyam;Krishna Kalyanam;David Casbeer

IEEE Transactions on Robotics
Year: 2023 | Volume: 39, Issue: 2 | Journal Article |
Cited by: Papers (5)
Persistent monitoring missions require an up-to-date knowledge of the changing state of the underlying environment. Unmannned aerial vehicles (UAVs) can be gainfully employed to continually visit a set of targets representing tasks (and locations) in the environment and collect data therein for long time periods. The enduring nature of these missions requires the UAV to be regularly recharged at a...Show More

Bounds on Optimal Revisit Times in Persistent Monitoring Missions With a Distinct and Remote Service Station

Sai Krishna Kanth Hari;Sivakumar Rathinam;Swaroop Darbha;Satyanarayana Gupta Manyam;Krishna Kalyanam;David Casbeer

Year: 2023 | Volume: 39, Issue: 2 | Journal Article |

A Conflict-Based Search Framework for Multiobjective Multiagent Path Finding

Zhongqiang Ren;Sivakumar Rathinam;Howie Choset

IEEE Transactions on Automation Science and Engineering
Year: 2023 | Volume: 20, Issue: 2 | Journal Article |
Cited by: Papers (19)
Conventional multi-agent path planners typically compute an ensemble of paths while optimizing a single objective, such as path length. However, many applications may require multiple objectives, say fuel consumption and completion time, to be simultaneously optimized during planning and these criteria may not be readily compared and sometimes lie in competition with each other. The goal of the pr...Show More

A Conflict-Based Search Framework for Multiobjective Multiagent Path Finding

Zhongqiang Ren;Sivakumar Rathinam;Howie Choset

Year: 2023 | Volume: 20, Issue: 2 | Journal Article |

A Reactive Energy-Aware Rendezvous Planning Approach for Multi-Vehicle Teams

Kenny Chour;Jean-Paul Reddinger;James Dotterweich;Marshal Childers;James Humann;Sivakumar Rathinam;Swaroop Darbha

2022 IEEE 18th International Conference on Automation Science and Engineering (CASE)
Year: 2022 | Conference Paper |
Cited by: Papers (2)
This paper addresses a type of rendezvous recharging problem involving a team of unmanned aerial and ground vehicles (UAVs, UGVs). UAVs are tasked with long-term surveillance and reactivity to events over a wide area, but are subject to energy constraints limiting their operation. UGVs can support UAVs by replenishing their battery via docking. The presented problem is a generalization of well-kno...Show More

A Reactive Energy-Aware Rendezvous Planning Approach for Multi-Vehicle Teams

Kenny Chour;Jean-Paul Reddinger;James Dotterweich;Marshal Childers;James Humann;Sivakumar Rathinam;Swaroop Darbha

Year: 2022 | Conference Paper |

Multi-Objective Safe-Interval Path Planning With Dynamic Obstacles

Zhongqiang Ren;Sivakumar Rathinam;Maxim Likhachev;Howie Choset

IEEE Robotics and Automation Letters
Year: 2022 | Volume: 7, Issue: 3 | Journal Article |
Cited by: Papers (16)
Path planning among dynamic obstacles is a fundamental problem in Robotics with numerous applications. In this work, we investigate a problem called Multi-Objective Path Planning with Dynamic Obstacles (MOPPwDO), which requires finding collision-free Pareto-optimal paths amid obstacles moving along known trajectories while simultaneously optimizing multiple conflicting objectives, such as arrival ...Show More

Multi-Objective Safe-Interval Path Planning With Dynamic Obstacles

Zhongqiang Ren;Sivakumar Rathinam;Maxim Likhachev;Howie Choset

Year: 2022 | Volume: 7, Issue: 3 | Journal Article |

Multi-Objective Path-Based D* Lite

Zhongqiang Ren;Sivakumar Rathinam;Maxim Likhachev;Howie Choset

IEEE Robotics and Automation Letters
Year: 2022 | Volume: 7, Issue: 2 | Journal Article |
Cited by: Papers (22)
Incrementalgraph search algorithms such as D* Lite reuse previous, and perhaps partial, searches to expedite subsequent path planning tasks. In this article, we are interested in developing incremental graph search algorithms for path finding problems to simultaneously optimize multiple objectives such as travel risk, arrival time, etc. This is challenging because in a multi-objective setting, the...Show More

Multi-Objective Path-Based D* Lite

Zhongqiang Ren;Sivakumar Rathinam;Maxim Likhachev;Howie Choset

Year: 2022 | Volume: 7, Issue: 2 | Journal Article |

String Stability of Connected Vehicle Platoons Under Lossy V2V Communication

Vamsi Vegamoor;Sivakumar Rathinam;Swaroop Darbha

IEEE Transactions on Intelligent Transportation Systems
Year: 2022 | Volume: 23, Issue: 7 | Journal Article |
Cited by: Papers (24)
Recent advances in vehicle connectivity have allowed formation of autonomous vehicle platoons for improved mobility and traffic throughput. In order to avoid a pile-up in such platoons, it is important to ensure platoon (string) stability, which is the focus of this work. As per conventional definition of string stability, the power (2-norm) of the spacing error signals should not amplify downstre...Show More

String Stability of Connected Vehicle Platoons Under Lossy V2V Communication

Vamsi Vegamoor;Sivakumar Rathinam;Swaroop Darbha

Year: 2022 | Volume: 23, Issue: 7 | Journal Article |

Loosely Synchronized Search for Multi-agent Path Finding with Asynchronous Actions

Zhongqiang Ren;Sivakumar Rathinam;Howie Choset

2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Year: 2021 | Conference Paper |
Cited by: Papers (10)
Multi-agent path finding (MAPF) determines an ensemble of collision-free paths for multiple agents between their respective start and goal locations. Among the available MAPF planners for workspace modeled as a graph, A*-based approaches have been widely investigated due to their guarantees on completeness and solution optimality, and have demonstrated their efficiency in many scenarios. However, ...Show More

Loosely Synchronized Search for Multi-agent Path Finding with Asynchronous Actions

Zhongqiang Ren;Sivakumar Rathinam;Howie Choset

Year: 2021 | Conference Paper |

MS*: A New Exact Algorithm for Multi-agent Simultaneous Multi-goal Sequencing and Path Finding

Zhongqiang Ren;Sivakumar Rathinam;Howie Choset

2021 IEEE International Conference on Robotics and Automation (ICRA)
Year: 2021 | Conference Paper |
Cited by: Papers (16)
In multi-agent applications such as surveillance and logistics, fleets of mobile agents are often expected to coordinate and safely visit a large number of goal locations as efficiently as possible. The multi-agent planning problem in these applications involves allocating and sequencing goals for each agent while simultaneously producing conflict-free paths for the agents. In this article, we int...Show More

MS*: A New Exact Algorithm for Multi-agent Simultaneous Multi-goal Sequencing and Path Finding

Zhongqiang Ren;Sivakumar Rathinam;Howie Choset

Year: 2021 | Conference Paper |

Multi-objective Conflict-based Search for Multi-agent Path Finding

Zhongqiang Ren;Sivakumar Rathinam;Howie Choset

2021 IEEE International Conference on Robotics and Automation (ICRA)
Year: 2021 | Conference Paper |
Cited by: Papers (11)
Conventional multi-agent path planners typically compute an ensemble of paths while optimizing a single objective, such as path length. However, many applications may require multiple objectives, say fuel consumption and completion time, to be simultaneously optimized during planning and these criteria may not be readily compared and sometimes lie in competition with each other. Naively applying e...Show More

Multi-objective Conflict-based Search for Multi-agent Path Finding

Zhongqiang Ren;Sivakumar Rathinam;Howie Choset

Year: 2021 | Conference Paper |

An Approximation Algorithm for an Assisted Shortest Path Problem

Christopher Montez;Sivakumar Rathinam;Swaroop Darbha;David Casbeer;Satyanarayana Gupta Manyam

2021 IEEE International Conference on Robotics and Automation (ICRA)
Year: 2021 | Conference Paper |
Cited by: Papers (1)
In this article, we introduce a cooperative path planning algorithm for a cardinal and a support robot where the cardinal robot is unable to traverse a subset of edges in a network until the support robot has first traversed them. This subset of edges represent paths in an environment that are initially unavailable to the cardinal robot and require the assistance of the support robot. A (2 + α)-ap...Show More

An Approximation Algorithm for an Assisted Shortest Path Problem

Christopher Montez;Sivakumar Rathinam;Swaroop Darbha;David Casbeer;Satyanarayana Gupta Manyam

Year: 2021 | Conference Paper |

Min-Max Task Assignment and Sequencing with Heterogeneous Unmanned Vehicles

Jarett Battistini;Sivakumar Rathinam;Richard Tatum

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)
Year: 2021 | Conference Paper |
Cited by: Papers (2)
This article addresses a planning problem for a team of heterogeneous, unmanned surface vehicles whose time costs are attributable to either transiting or task execution costs. Given a set of target regions and a team of unmanned vehicles, the Heterogeneous Multi-vehicle Planning Problem (HMPP) aims to find a tour for each vehicle such that each target is visited at least once by some vehicle and ...Show More

Min-Max Task Assignment and Sequencing with Heterogeneous Unmanned Vehicles

Jarett Battistini;Sivakumar Rathinam;Richard Tatum

Year: 2021 | Conference Paper |

Subdimensional Expansion for Multi-Objective Multi-Agent Path Finding

Zhongqiang Ren;Sivakumar Rathinam;Howie Choset

IEEE Robotics and Automation Letters
Year: 2021 | Volume: 6, Issue: 4 | Journal Article |
Cited by: Papers (13)
Conventional multi-agent path planners typically determine a path that optimizes a single objective, such as path length. Many applications, however, may require multiple objectives, say time-to-completion and fuel use, to be simultaneously optimized in the planning process. Often, these criteria may not be directly compared and sometimes lie in competition with each other. Simply applying standar...Show More

Subdimensional Expansion for Multi-Objective Multi-Agent Path Finding

Zhongqiang Ren;Sivakumar Rathinam;Howie Choset

Year: 2021 | Volume: 6, Issue: 4 | Journal Article |

Optimal UAV Route Planning for Persistent Monitoring Missions

Sai Krishna Kanth Hari;Sivakumar Rathinam;Swaroop Darbha;Krishna Kalyanam;Satyanarayana Gupta Manyam;David Casbeer

IEEE Transactions on Robotics
Year: 2021 | Volume: 37, Issue: 2 | Journal Article |
Cited by: Papers (29)
This article addresses a persistent monitoring problem (PMP) that requires an unmanned aerial vehicle (UAV) to repeatedly visit n targets of equal priority. The UAV has limited onboard fuel/charge and must be regularly serviced at a depot. Given a fixed number of visits, k, for the UAV to the targets between successive services, the objective of the PMP is to determine an optimal sequence of visit...Show More

Optimal UAV Route Planning for Persistent Monitoring Missions

Sai Krishna Kanth Hari;Sivakumar Rathinam;Swaroop Darbha;Krishna Kalyanam;Satyanarayana Gupta Manyam;David Casbeer

Year: 2021 | Volume: 37, Issue: 2 | Journal Article |

Lateral Control of an Autonomous and Connected Following Vehicle With Limited Preview Information

Mengke Liu;Kenny Chour;Sivakumar Rathinam;Swaroop Darbha

IEEE Transactions on Intelligent Vehicles
Year: 2021 | Volume: 6, Issue: 3 | Journal Article |
Cited by: Papers (14)
Lateral control of an autonomous and connected vehicle (ACV), especially in emergency situations, is important from the safety viewpoint. In these situations, the trajectory to be followed by an ACV must either be planned in real-time (e.g., for a possible evasion maneuver if the obstacle to be avoided is detected) or be communicated from its preceding vehicle. Typically, the trajectory informatio...Show More

Lateral Control of an Autonomous and Connected Following Vehicle With Limited Preview Information

Mengke Liu;Kenny Chour;Sivakumar Rathinam;Swaroop Darbha

Year: 2021 | Volume: 6, Issue: 3 | Journal Article |

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