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Proper path planning is the first step of robust and efficient autonomous navigation for mobile robots. Meanwhile, it is still challenging for robots to work in a complex environment without complete prior information. This paper presents…

Robotics · Computer Science 2020-09-17 Wenjian Hao , Rongyao Wang , Alexander Krolicki , Yiqiang Han

Autonomous exploration of unknown environments has been widely applied in inspection, surveillance, and search and rescue. In exploration task, the basic requirement for robots is to detect the unknown space as fast as possible. In this…

Robotics · Computer Science 2021-09-13 Luqi Wang , Daqian Cheng , Fei Gao , Fengyu Cai , Jixin Guo , Mengxiang Lin , Shaojie Shen

With technological advancement, drone has emerged as unmanned aerial vehicle that can be controlled by humans to fly or reach a destination. This may be autonomous as well, where the drone itself is intelligent enough to find a shortest…

Artificial Intelligence · Computer Science 2021-12-06 Prithwish Jana , Debasish Jana

We present a method for solving the coverage problem with the objective of autonomously exploring an unknown environment under mission time constraints. Here, the robot is tasked with planning a path over a horizon such that the accumulated…

In this paper we address the problem of path planning in an unknown environment with an aerial robot. The main goal is to safely follow the planned trajectory by avoiding obstacles. The proposed approach is suitable for aerial vehicles…

Robotics · Computer Science 2023-06-29 Ana Batinovic , Jurica Goricanec , Lovro Markovic , Stjepan Bogdan

An important capability of autonomous Unmanned Aerial Vehicles (UAVs) is autonomous landing while avoiding collision with obstacles in the process. Such capability requires real-time local trajectory planning. Although trajectory-planning…

Robotics · Computer Science 2021-11-19 Yossi Magrisso , Ehud Rivlin , Hector Rotstein

Path planning in dynamic environments is essential to high-risk applications such as unmanned aerial vehicles, self-driving cars, and autonomous underwater vehicles. In this paper, we generate collision-free trajectories for a robot within…

Robotics · Computer Science 2020-07-30 Sourav Dutta , Tuan Tran , Banafsheh Rekabdar , Chinwe Ekenna

In this paper, we address the problem of safe trajectory planning for autonomous search and exploration in constrained, cluttered environments. Guaranteeing safe (collision-free) trajectories is a challenging problem that has garnered…

Robotics · Computer Science 2023-05-02 Cameron Lerch , Dayi Dong , Ian Abraham

This work presents an innovative solution for robotic odometry, path planning and exploration in wild unknown environments, focusing on digital modelling. The approach uses a minimum cost formulation with pseudo-randomly generated…

Robotics · Computer Science 2024-03-29 Naizhong Zhang. Yaoqiang Pan , Yangwen Jin , Peiqi Jin , Kewei Hu , Xiao Huang , Hanwen Kang

Exploration and mapping of unknown environments is a fundamental task in applications for autonomous robots. In this article, we present a complete framework for deploying MAVs in autonomous exploration missions in unknown subterranean…

This paper presents a self-contained system for the robust utilization of aerial robots in the autonomous exploration of cave environments to help human explorers, first responders, and speleologists. The proposed system is generally…

Robotics · Computer Science 2023-03-07 Pavel Petracek , Vit Kratky , Matej Petrlik , Tomas Baca , Radim Kratochvil , Martin Saska

This paper presents an autonomous navigation framework for reaching a goal in unknown 3D cluttered environments. The framework consists of three main components. First, a computationally efficient method for mapping the environment from the…

Unmanned aerial vehicle (UAV) path planning enables UAVs to avoid obstacles and reach the target efficiently. To generate high-quality paths without obstacle collision for UAVs, this paper proposes a novel autonomous path planning algorithm…

Robotics · Computer Science 2020-06-09 Huan Liu , Xiamiao Li , Mingfeng Fan , Guohua Wu , Witold Pedrycz , Ponnuthurai Nagaratnam Suganthan

Autonomous exploration requires robots to generate informative trajectories iteratively. Although sampling-based methods are highly efficient in unmanned aerial vehicle exploration, many of these methods do not effectively utilize the…

Robotics · Computer Science 2021-03-23 Zhefan Xu , Di Deng , Kenji Shimada

Autonomous exploration of unknown space is an essential component for the deployment of mobile robots in the real world. Safe navigation is crucial for all robotics applications and requires accurate and consistent maps of the robot's…

Robotics · Computer Science 2026-01-13 Sotiris Papatheodorou , Simon Boche , Sebastián Barbas Laina , Stefan Leutenegger

Autonomous exploration using unmanned aerial vehicles (UAVs) is essential for various tasks such as building inspections, rescue operations, deliveries, and warehousing. However, there are two main limitations to previous approaches: they…

Safe autonomous navigation is an essential and challenging problem for robots operating in highly unstructured or completely unknown environments. Under these conditions, not only robotic systems must deal with limited localisation…

Robotics · Computer Science 2020-05-27 Èric Pairet , Juan David Hernández , Marc Carreras , Yvan Petillot , Morteza Lahijanian

Full autonomy for fixed-wing unmanned aerial vehicles (UAVs) requires the capability to autonomously detect potential landing sites in unknown and unstructured terrain, allowing for self-governed mission completion or handling of emergency…

Robotics · Computer Science 2018-02-27 Timo Hinzmann , Thomas Stastny , Cesar Cadena , Roland Siegwart , Igor Gilitschenski

Tunnel construction using the drill-and-blast method requires the 3D measurement of the excavation front to evaluate underbreak locations. Considering the inspection and measurement task's safety, cost, and efficiency, deploying lightweight…

Robotics · Computer Science 2024-01-17 Zhefan Xu , Baihan Chen , Xiaoyang Zhan , Yumeng Xiu , Christopher Suzuki , Kenji Shimada

We show a new method for collision-free path planning by cGANs by mapping its latent space to only the collision-free areas of the robot joint space. Our method simply provides this collision-free latent space after which any planner, using…

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