Kashish Garg

dblp:210/6025 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2025
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
2 papers
Multi-agent systems · 100%
Computer networks
1 paper
Wireless networking · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Multi-agent systems
multi-robot coordination
0.912025
Online Multirobot Coordination and Cooperation With Task Precedence Relationships · IEEE Trans. Robotics 2025
Wireless networking
opportunistic communication
0.812024
Opportunistic Communication in Robot Teams · ICRA 2024
Knowledge, reasoning and agents › Multi-agent systems › task allocation
cooperative task allocation
0.312025
Online Multirobot Coordination and Cooperation With Task Precedence Relationships · IEEE Trans. Robotics 2025
Knowledge, reasoning and agents › Multi-agent systems › multi-robot systems
multi-robot team
0.212024
Opportunistic Communication in Robot Teams · ICRA 2024
Knowledge, reasoning and agents › Multi-agent systems
wireless connectivity
0.212024
Opportunistic Communication in Robot Teams · ICRA 2024

Methods — techniques the papers use, named apart from their topics

packet delivery probability maximization · 1.5opportunistic routing · 1.5
YearPublicationVenuePosition
2025 Online Multirobot Coordination and Cooperation With Task Precedence Relationships
Walker Gosrich, Saurav Agarwal, Kashish Garg, Siddharth Mayya, Matthew Malencia, Mark Yim, Vijay Kumar 0001
IEEE Trans. Robotics3
2024 Opportunistic Communication in Robot Teams
abstract
In this paper we present a new approach to Mobile Infrastructure on Demand (MID) where a dedicated team of robots creates and sustains a wireless network that satisfies the communication requirements of a different team of task-oriented robots seeking to coordinate their actions in the absence of existing communication infrastructure. Different from previous works, our approach forgoes heuristics for network performance such as algebraic-connectivity or network flow optimizations and instead positions communication support robots to directly maximize the probability of packet delivery by the underlying opportunistic routing protocol. Our system is task agnostic and practical to implement and operate on robots equipped with off-the-shelf WiFi radios. We demonstrate this through a set of experiments showing our MID system maintaining the delivery of critical mission data in a situational awareness setting and enabling foraging robots to effectively coordinate their actions during multi-robot exploration.
Daniel Mox, Kashish Garg, Alejandro Ribeiro, Vijay Kumar 0001
ICRA2