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The advances in deep reinforcement learning recently revived interest in data-driven learning based approaches to navigation. In this paper we propose to learn viewpoint invariant and target invariant visual servoing for local mobile robot…

Computer Vision and Pattern Recognition · Computer Science 2020-03-06 Yimeng Li , Jana Kosecka

Visual servoing, the method of controlling robot motion through feedback from visual sensors, has seen significant advancements with the integration of optical flow-based methods. However, its application remains limited by inherent…

Modern-day surveillance systems perform person recognition using deep learning-based face verification networks. Most state-of-the-art facial verification systems are trained using visible spectrum images. But, acquiring images in the…

Computer Vision and Pattern Recognition · Computer Science 2022-09-20 Nithin Gopalakrishnan Nair , Vishal M. Patel

Existing deep learning based visual servoing approaches regress the relative camera pose between a pair of images. Therefore, they require a huge amount of training data and sometimes fine-tuning for adaptation to a novel scene.…

Robotics · Computer Science 2020-03-10 Y V S Harish , Harit Pandya , Ayush Gaud , Shreya Terupally , Sai Shankar , K. Madhava Krishna

Autonomous vehicles (AVs) are expected to revolutionize transportation by improving efficiency and safety. Their success relies on 3D vision systems that effectively sense the environment and detect traffic agents. Among sensors AVs use to…

Computer Vision and Pattern Recognition · Computer Science 2025-09-24 Amirhesam Aghanouri , Cristina Olaverri-Monreal

Visual servoing enables robotic systems to perform accurate closed-loop control, which is required in many applications. However, existing methods either require precise calibration of the robot kinematic model and cameras or use neural…

In this paper we propose an effective vision-based navigation method that allows a multirotor vehicle to simultaneously reach a desired goal pose in the environment while constantly facing a target object or landmark. Standard techniques…

Robotics · Computer Science 2018-01-26 Ciro Potena , Daniele Nardi , Alberto Pretto

This paper presents an image-based visual servo control (IBVS) method for a first-person-view (FPV) quadrotor to conduct aggressive aerial tracking. There are three major challenges to maneuvering an underactuated vehicle using IBVS: (i)…

Robotics · Computer Science 2022-12-20 Chao Qin , Qiuyu Yu , Hugh H. T. Liu

Classical Visual Servoing (VS) rely on handcrafted visual features, which limit their generalizability. Recently, a number of approaches, some based on Deep Neural Networks, have been proposed to overcome this limitation by comparing…

Robotics · Computer Science 2022-01-21 Nicholas Adrian , Van-Thach Do , Quang-Cuong Pham

Many aerial robotic applications require the ability to land on moving platforms, such as delivery trucks and marine research boats. We present a method to autonomously land an Unmanned Aerial Vehicle on a moving vehicle. A visual servoing…

We propose a visual servoing method consisting of a detection network and a velocity trajectory planner. First, the detection network estimates the objects position and orientation in the image space. Furthermore, these are normalized and…

Robotics · Computer Science 2024-12-13 Constantin Schempp , Christian Friedrich

A novel prize-winner algorithm designed for a path following problem within the Unmanned Aerial Vehicle (UAV) field is presented in this paper. The proposed approach exploits the advantages offered by the pure pursuing algorithm to set up…

The photovoltaic (PV) industry is seeing a significant shift toward large-scale solar plants, where traditional inspection methods have proven to be time-consuming and costly. Currently, the predominant approach to PV inspection using…

Route planning for navigation under partial observability plays a crucial role in modern robotics and autonomous driving. Existing route planning approaches can be categorized into two main classes: traditional autoregressive and…

Robotics · Computer Science 2024-04-04 Gengyu Zhang , Hao Tang , Yan Yan

3D Move To See (3DMTS) is a mutli-perspective visual servoing method for unstructured and occluded environments, like that encountered in robotic crop harvesting. This paper presents a deep learning method, Deep-3DMTS for creating a…

Robotics · Computer Science 2019-08-07 Paul Zapotezny-Anderson , Chris Lehnert

Visual servoing techniques guide robotic motion using visual information to accomplish manipulation tasks, requiring high precision and robustness against noise. Traditional methods often require prior knowledge and are susceptible to…

Robotics · Computer Science 2026-02-24 Haoyu Zhang , Yang Liu , Yimu Jiang , Weiyang Lin , Chao Ye

Visual traversability estimation is critical for autonomous navigation, but existing VLM-based methods rely on hand-crafted prompts, generalize poorly across embodiments, and output only traversability maps, leaving trajectory generation to…

Novel view synthesis (NVS) seeks to render photorealistic, 3D-consistent images of a scene from unseen camera poses given only a sparse set of posed views. Existing deterministic networks render observed regions quickly but blur unobserved…

Computer Vision and Pattern Recognition · Computer Science 2025-12-24 Thanh-Tung Le , Tuan Pham , Tung Nguyen , Deying Kong , Xiaohui Xie , Stephan Mandt

This article proposes a method to diminish the pose (position plus attitude) drift experienced by an SVO (Semi-Direct Visual Odometry) based visual navigation system installed onboard a UAV (Unmanned Air Vehicle) by supplementing its pose…

Robotics · Computer Science 2023-03-03 Eduardo Gallo , Antonio Barrientos

Robust and accurate localization for Unmanned Aerial Vehicles (UAVs) is an essential capability to achieve autonomous, long-range flights. Current methods either rely heavily on GNSS, face limitations in visual-based localization due to…

Robotics · Computer Science 2023-10-26 Yao He , Ivan Cisneros , Nikhil Keetha , Jay Patrikar , Zelin Ye , Ian Higgins , Yaoyu Hu , Parv Kapoor , Sebastian Scherer
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