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Akshit Saradagi

10 accepted papers

2026

Deployment of an Aerial Multiagent System for Automated Task Execution in Large-Scale Underground Mining Environments (I)

Niklas Dahlquist, Samuel Nordström, Nikolaos Stathoulopoulos, Björn Lindqvist, Akshit Saradagi, George Nikolakopoulos
ICRA 2026poster

In this article, we present a framework for deploying aerial multiagent systems in large-scale subterranean environments with minimal supporting infrastructure. The objective is to optimally and reactively execute routine inspection tasks, selected by a mine operator on-the-fly. The assignment of cu…

Cited by 0Scholar ↗
2025

LLM-Informed Iterative Planning for Object Search and Relocation in Indoor Environments

Taxiarchis-Foivos Blounas, Akshit Saradagi, George Nikolakopoulos
IROS 2025

The process of object search and relocation in an indoor environment, while intuitive for humans, remains a complex challenge for robots. Enabling robots to perform this task autonomously could have a substantial impact towards automation in both domestic and industrial settings. In this article, as

Cited by 0Source ↗Scholar ↗
2025

Multi-Agent Path Finding Using Conflict-Based Search and Structural-Semantic Topometric Maps

Scott Fredriksson, Yifan Bai, Akshit Saradagi, George Nikolakopoulos
ICRA 2025

As industries increasingly adopt large robotic fleets, there is a pressing need for computationally efficient, practical, and optimal conflict-free path planning for multiple robots. Conflict-Based Search (CBS) is a popular method for multi-agent path finding (MAPF) due to its completeness and optim

Cited by 2Source ↗Scholar ↗
2024

A CBF-Adaptive Control Architecture for Visual Navigation for UAV in the Presence of Uncertainties

Viswa Narayanan Sankaranarayanan, Akshit Saradagi, Sumeet Satpute, George Nikolakopoulos
ICRA 2024poster

In this article, we propose a control solution for the safe transfer of a quadrotor UAV between two surface robots positioning itself only using the visual features on the surface robots, which enforces safety constraints for precise landing and visual locking, in the presence of modeling uncertaint…

Cited by 4Source ↗Scholar ↗
2024

Behavior Tree Based Decentralized Multi-agent Coordination for Balanced Servicing of Time Varying Task Queues

Niklas Dahlquist, Akshit Saradagi, George Nikolakopoulos
IROS 2024poster

In this article, we present a reactive multi-agent coordination architecture for the management of material flows between production/pickup stages and delivery/drop-off stages, in scenarios such as underground mines and automated factory floors. The pickup and delivery stages are modelled as variabl…

Cited by 0Source ↗Scholar ↗
2024

Belief Scene Graphs: Expanding Partial Scenes with Objects through Computation of Expectation

Mario A.V. Saucedo, Akash Patel, Akshit Saradagi, Christoforos Kanellakis, George Nikolakopoulos
ICRA 2024poster

In this article, we propose the novel concept of Belief Scene Graphs, which are utility-driven extensions of partial 3D scene graphs, that enable efficient high-level task planning with partial information. We propose a graph-based learning methodology for the computation of belief (also referred to…

Cited by 5Source ↗Scholar ↗
2024

Environmental Awareness Dynamic 5G QoS for Retaining Real Time Constraints in Robotic Applications

Gerasimos Damigos, Akshit Saradagi, Sara Sandberg, George Nikolakopoulos
ICRA 2024poster

The fifth generation (5G) cellular network technology is mature and increasingly utilized in many industrial and robotics applications, while an important functionality is the advanced Quality of Service (QoS) features. Despite the prevalence of 5G QoS discussions in the related literature, there is…

Cited by 1Source ↗Scholar ↗
2024

Time-varying Control Barrier Function for Safe and Precise Landing of a UAV on a Moving Target

Viswa Narayanan Sankaranarayanan, Akshit Saradagi, Sumeet Satpute, George Nikolakopoulos
IROS 2024poster

In this article, we present a control barrier function (CBF)-based control strategy for safe and precise landing of an unmanned aerial vehicle (UAV) on a moving target. The CBF is time-varying, as it depends on the velocity of the landing platform and captures three crucial safety constraints: (a) c…

Cited by 1Source ↗Scholar ↗
2024

Voxel Map to Occupancy Map Conversion Using Free Space Projection for Efficient Map Representation for Aerial and Ground Robots

Scott Fredriksson, Akshit Saradagi, George Nikolakopoulos
RA-L 2024

This article introduces a novel method for converting 3D voxel maps, commonly utilized by robots for localization and navigation, into 2D occupancy maps for both autonomous aerial vehicles (AAVs) and autonomous ground vehicles (AGVs). The generated 2D maps can be used for more efficient global navig

Cited by 8Source ↗Scholar ↗