39 citations · 86 across the 18 of their papers we have counts for
22 papers
Correcting and Quantifying Systematic Errors in 3D Box Annotations for Autonomous Driving
Alexandre Justo Miro, Ludvig af Klinteberg, Bogdan Timus +5
Accurate ground truth annotations are critical to supervised learning and evaluating the performance of autonomous vehicle systems. These vehicles are typically equipped with activ…
Batch Prompting Suppresses Overthinking Reasoning Under Constraint: How Batch Prompting Suppresses Overthinking in Reasoning Models
Saurabh Srivastava, Janit Bidhan, Hao Yan +7
Large Reasoning Models (LRMs) achieve strong performance through explicit chain-of-thought reasoning but suffer from \textit{overthinking}: generating excessive reasoning tokens ev…
DoGFlow: Self-Supervised LiDAR Scene Flow via Cross-Modal Doppler Guidance
Ajinkya Khoche, Qingwen Zhang, Yixi Cai +2
Accurate 3D scene flow estimation is critical for autonomous systems to navigate dynamic environments safely, but creating the necessary large-scale, manually annotated datasets re…
AutoScale: Linear Scalarization Guided by Multi-Task Optimization Metrics
Yi Yang, Kei Ikemura, Qingwen Zhang +5
Recent multi-task learning studies suggest that linear scalarization, when using well-chosen fixed task weights, can achieve comparable to or even better performance than complex m…
HiMo: High-Speed Objects Motion Compensation in Point Clouds
Qingwen Zhang, Ajinkya Khoche, Yi Yang +4
LiDAR point cloud is essential for autonomous vehicles, but motion distortions from dynamic objects degrade the data quality. While previous work has considered distortions caused…
SSF: Sparse Long-Range Scene Flow for Autonomous Driving
Ajinkya Khoche, Qingwen Zhang, Laura Pereira Sanchez +3
Scene flow enables an understanding of the motion characteristics of the environment in the 3D world. It gains particular significance in the long-range, where object-based percept…
Addressing Data Annotation Challenges in Multiple Sensors: A Solution for Scania Collected Datasets
Ajinkya Khoche, Aron Asefaw, Alejandro Gonzalez +3
Data annotation in autonomous vehicles is a critical step in the development of Deep Neural Network (DNN) based models or the performance evaluation of the perception system. This…
Towards Long-Range 3D Object Detection for Autonomous Vehicles
Ajinkya Khoche, Laura Pereira Sánchez, Nazre Batool +2
3D object detection at long range is crucial for ensuring the safety and efficiency of self driving vehicles, allowing them to accurately perceive and react to objects, obstacles,…
Multi-Stage NMPC for a MAV based Collision Free Navigation under Varying Communication Delays
Andreas Papadimitriou, Hedyeh Jafari, Sina Sharif Mansouri +1
Time delays in communication networks are one of the main concerns in deploying robots with computation boards on the edge. This article proposes a multi-stage Nonlinear Model Pred…
Reactive Navigation of an Unmanned Aerial Vehicle with Perception-based Obstacle Avoidance Constraints
Björn Lindqvist, Sina Sharif Mansouri, Jakub Haluška +1
In this article we propose a reactive constrained navigation scheme, with embedded obstacles avoidance for an Unmanned Aerial Vehicle (UAV), for enabling navigation in obstacle-den…
Collision avoidance for multiple MAVs using fast centralized NMPC
Björn Lindqvist, Sina Sharif Mansouri, Pantelis Sopasakis +1
This article proposes a novel control architecture using a centralized nonlinear model predictive control (CNMPC) scheme for controlling multiple micro aerial vehicles (MAVs). The…
COMPRA: A COMPact Reactive Autonomy framework for subterranean MAV based search-and-rescue operations
Björn Lindqvist, Christoforos Kanellakis, Sina Sharif Mansouri +2
This work establishes COMPRA, a compact and reactive autonomy framework for fast deployment of Micro Aerial Vehicles (MAVs) in subterranean Search-and-Rescue (SAR) missions. A COMP…
Geometry Aware NMPC Scheme for Morphing Quadrotor Navigation in Restricted Entrances
Andreas Papadimitriou, Sina Sharif Mansouri, Christoforos Kanellakis +1
Geometry-morphing Micro Aerial Vehicles (MAVs) are gaining more and more attention lately, since their ability to modify their geometric morphology in-flight increases their versat…
Nonlinear MPC for Collision Avoidance and Controlof UAVs With Dynamic Obstacles
Björn Lindqvist, Sina Sharif Mansouri, Ali-akbar Agha-mohammadi +1
This article proposes a Novel Nonlinear Model Predictive Control (NMPC) for navigation and obstacle avoidance of an Unmanned Aerial Vehicle (UAV). The proposed NMPC formulation all…
A Unified NMPC Scheme for MAVs Navigation with 3D Collision Avoidance under Position Uncertainty
Sina Sharif Mansouri, Christoforos Kanellakis, Bjorn Lindqvist +4
This article proposes a novel Nonlinear Model Predictive Control (NMPC) framework for Micro Aerial Vehicle (MAV) autonomous navigation in constrained environments. The introduced f…
Subterranean MAV Navigation based on Nonlinear MPC with Collision Avoidance Constraints
Sina Sharif Mansouri, Christoforos Kanellakis, Emil Fresk +5
Micro Aerial Vehicles (MAVs) navigation in subterranean environments is gaining attention in the field of aerial robotics, however there are still multiple challenges for collision…
Unsupervised Learning for Subterranean Junction Recognition Based on 2D Point Cloud
Sina Sharif Mansouri, Farhad Pourkamali-Anaraki, Miguel Castano Arranz +3
This article proposes a novel unsupervised learning framework for detecting the number of tunnel junctions in subterranean environments based on acquired 2D point clouds. The imple…
MAV Navigation in Unknown Dark Underground Mines Using Deep Learning
Sina Sharif Mansouri, Christoforos Kanellakis, Petros Karvelis +2
This article proposes a Deep Learning (DL) method to enable fully autonomous flights for low-cost Micro Aerial Vehicles (MAVs) in unknown dark underground mine tunnels. This kind o…
MAV Development Towards Navigation in Unknown and Dark Mining Tunnels
Dariusz Kominiak, Sina Sharif Mansouri, Christoforos Kanellakis +1
The Mining industry considers the deployment of MAV for autonomous inspection of tunnels and shafts to increase safety and productivity. However, mines are challenging and harsh en…
Visual Area Coverage with Attitude-Dependent Camera Footprints by Particle Harvesting
Sina Sharif Mansouri, Pantelis Sopasakis, George Georgoulas +2
In aerial visual area coverage missions, the camera footprint changes over time based on the camera position and orientation -- a fact that complicates the whole process of coverag…
Autonomous visual inspection of large-scale infrastructures using aerial robots
Christoforos Kanellakis, Emil Fresk, Sina Sharif Mansouri +2
This article presents a novel framework for performing visual inspection around 3D infrastructures, by establishing a team of fully autonomous Micro Aerial Vehicles (MAVs) with rob…
Cooperative Aerial Coverage Path Planning for Visual Inspection of Complex Infrastructures
Sina Sharif Mansouri, Christoforos Kanellakis, David Wuthier +2
This article addresses the problem of Cooperative Coverage Path Planning (C-CPP) for the inspection of complex infrastructures (offline 3D reconstruction) by utilizing multiple Unm…