Livestock management is an emerging area of application of the quadrotor, especially for monitoring, counting, detecting, recognizing, and tracking animals through image or video footage. The autonomous operation of the quadrotor requires the develop...
With the widespread adoption of the Robot Operating System (ROS), technologies for autonomous navigation in mobile robots have advanced considerably. ROS provides a modular navigation stack that integrates essential components, such as SLAM, localisa...
This paper takes autonomous exploration in unknown environments on a small co-axial twin-rotor unmanned aerial vehicle (UAV) platform as the task. The study of the fully autonomous positioning in unknown environments and navigation system without glo...
In recent years, autonomous robots have extensively been used to automate several vineyard tasks. Autonomous navigation is an indispensable component of such field robots. Autonomous and safe navigation has been well studied in indoor environments an...
The industry is changing in order to improve the economy sector. This is the reason why technology is improving and developing new devices. The autonomous guided vehicle with free navigation is a new machine, which uses different techniques to move s...
Obstacle avoidance control and navigation in unstructured agricultural environments are key to the safe operation of autonomous robots, especially for agricultural machinery, where cost and stability should be taken into account. In this paper, we de...
Path planning creates the shortest path from the source to the destination based on sensory information obtained from the environment. Within path planning, obstacle avoidance is a crucial task in robotics, as the autonomous operation of robots needs...
For robots to navigate effectively in human-shared spaces, they should follow behavioral rules that not only prevent collisions with humans but also reduce uncertainty about the robot’s actions. These rules should be grounded in human collision...
Dynamic obstacle avoidance is essential for unmanned surface vehicles (USVs) to achieve autonomous sailing. This paper presents a dynamic navigation ship domain (DNSD)-based dynamic obstacle avoidance approach for USVs in compliance with COLREGs. Bas...
Autonomous drone navigation presents challenges for users unfamiliar with manual flight controls, increasing the risk of collisions. This research addresses this issue by developing a multifunctional drone control system that integrates hand gesture...
Autonomous navigation for micro electric vehicles (micro EVs) operating in semi-structured environments—such as university campuses and industrial parks—requires solutions that are cost-effective, low in complexity, and robust. Traditiona...
High-speed near-ground flight presents critical challenges for large-inertia UAVs carrying payloads, including complex obstacles and communication-denied environments. Unlike agile small drones, these platforms require both rapid path planning and st...
For efficient and safe navigation for an autonomous surface vehicle (ASV), this paper proposes an autonomous navigation behavior framework that integrates deep reinforcement learning (DRL) to achieve autonomous decision-making and low-level control a...
With the growing application of unmanned aerial vehicles (UAVs) in complex, stochastic environments, autonomous navigation and obstacle avoidance represent critical technical challenges requiring urgent solutions. This study proposes an innovative de...
Flocking navigation and obstacle avoidance in complex environments remain challenging for multiple unmanned aerial vehicle (multi-UAV) systems, especially when only one UAV (termed as information UAV) knows the predetermined path and the communicatio...
We propose a tri-fold learning algorithm, called Neuroevolution of Hybrid Neural Networks in a Robotic Agent (acronym in Spanish, NRNH-AR), based on deep reinforcement learning (DRL), with self-supervised learning (SSL) and unsupervised learning (USL...
This paper focuses on safe navigation of an unmanned surface vehicle in proximity to a submerged autonomous underwater vehicle so as to maximise short-range, through-water data transmission while minimising the probability that the two vehicles will...
A comprehensive analysis of three graph-theoretic path planning algorithms designed for multi-robotic systems (MRS) was undertaken. The algorithms were the multi-robot path planning algorithm (MRPP), central algorithm (CA), and the optimisation centr...
Obstacle avoidance operations of tractors can cause parts of land to be unavailable for planting crops, which represents a reduction in land utilization. However, land utilization is significant to the increase in agricultural productivity. Tradition...
This paper presents a systematic reward engineering methodology for training a Proximal Policy Optimization (PPO) quadrotor navigation policy in the Webots simulator, using a hierarchical architecture in which a PID controller handles low-level stabi...
This paper presents a robust control strategy based on simplified second-order sliding mode for autonomous navigation and obstacle avoidance for an unmanned ground vehicle. The proposed control is implemented in a mini ground vehicle equipped with re...
To address the challenges of manual buoy inspection, this study enhances a previously proposed Unmanned Surface Vehicle (USV) inspection system by improving its navigation and obstacle avoidance capabilities using Proximal Policy Optimization (PPO)....
In order to prevent ship collisions, it is important to understand the behavior of navigators that leads to these collisions. The main cause of marine accidents in the Republic of Korea is attributed to navigator error, particularly in collisions. He...
People with disabilities (PWD) face a number of challenges such as obstacle avoidance or taking a minimum path to reach a destination while travelling or taking public transport, especially in airports or bus stations. In some cases, PWD, and specifi...
The collision avoidance system is one of the core systems of MASS (Maritime Autonomous Surface Ships). The collision avoidance system was validated using scenario-based experiments. However, the scenarios for the validation were designed based on COL...
Existing push robots mainly use magnetic induction technology. These devices are susceptible to external electromagnetic interference and have a low degree of intelligence. To make up for the insufficiency of the existing material pushing robots, and...
Autonomous multi-drone navigation in unknown environments requires robust solutions for obstacle avoidance, formation cohesion, and inter-drone communication maintenance. We address these challenges using Riemannian Motion Policies (RMPs), a second-o...
In this work, we propose an approach for the autonomous navigation of mobile robots using fusion the of sensor data by a Double Deep Q-Network with collision avoidance by detecting moving people via computer vision techniques. We evaluate two data fu...
Autonomous wheelchair navigation requires both reliable global guidance and safe local interaction with the environment, typically addressed using separate perception and control strategies. This paper presents a unified vision-based control framewor...
This paper presents a distributed closed-form control strategy for multi-unmanned aerial vehicle (multi-UAV) formation flight in cluttered environments. We propose a virtual-centroid-based architecture that reduces leader dependency while maintaining...
Many achievements toward unmanned surface vehicles have been made using artificial intelligence theory to assist the decisions of the navigator. In particular, there has been rapid development in autonomous collision avoidance techniques that employ...
To address the challenges of low pesticide utilization, insufficient automation, and health risks in orchard plant protection, we developed an autonomous spraying vehicle using ArduPilot firmware and a robot operating system (ROS). The system tackles...
In this work, we present a complete hybrid navigation system for a two-wheel differential drive mobile robot that includes static-environment- global-path planning and dynamic environment obstacle-avoidance tasks. By the given map, we propose a multi...
Autonomous unmanned-aircraft obstacle avoidance is a mature research area, but comparatively less work addresses controller-level behavior motivated by European ground-risk and no-overflight considerations during an inspection mission that is already...
This paper presents a 3D vision-based autonomous navigation system for wheeled mobile robots equipped with an RGB-D camera. The system integrates SLAM (simultaneous localization and mapping), motion planning, and obstacle avoidance to operate in both...
This paper introduces a practical navigation approach for nonholonomic Unmanned Aerial Vehicles (UAVs) in 3D environment settings with numerous stationary and dynamic obstacles. To achieve the intended outcome, Dynamic Programming (DP) is combined wi...
In this paper, a novel and complete navigation system is proposed for mobile robots in a park environment, which can achieve safe and stable navigation as well as robust dynamic obstacle avoidance. The navigation system includes a global planning lay...
Reinforcement learning (RL) represents an effective approach for developing autonomous navigation and obstacle avoidance capabilities in hospital automated guided vehicles (AGVs). However, real-world adoption is challenged by the need for carefully d...
To address the challenges of formation maintenance, collision avoidance, and cooperative navigation for multi-agent systems in shared environments, a spatio-temporal trajectory optimization method under global structural constraints and A attention-e...
Perhaps the most problematic issue regarding navigation safety management is the unknown, or unknowable, is the navigator’s decision made in the face of a dangerous situation. This applies particularly to collision-avoidance. The aim of the article i...
This paper investigates the safe navigation of mobile robots in complex-static-obstacle environments and proposes a deadlock-resistant navigation control method. First, convex polygonal obstacles are modeled using the Log-Sum-Exp (LSE) function. Goal...
This research focuses on the adaptive navigation of maritime autonomous surface ships (MASSs) in an uncertain environment. To achieve intelligent obstacle avoidance of MASSs in a port, an autonomous navigation decision-making model based on hierarchi...
In this paper, we propose a goal-oriented obstacle avoidance navigation system based on deep reinforcement learning that uses depth information in scenes, as well as goal position in polar coordinates as state inputs. The control signals for robot mo...
Higher requirements have been placed on fault detection for continuously operating machines in modern factories. Manual inspection faces challenges related to timeliness, leading to the emergence of autonomous diagnostic robots. To overcome the safet...
The integration of machine learning and robotics brings promising potential to tackle the application challenges of mobile robot navigation in industries. The real-world environment is highly dynamic and unpredictable, with increasing necessities for...
The paper introduces a proposal of an Autonomous Navigation System for Unmanned Surface Vessels. The system architecture is presented with a special emphasis on collision avoidance and maneuver auto-negotiation. For the purpose of maneuver auto-negot...
Path planning and collision avoidance during autonomous navigation in unknown environments is a crucial issue for unmanned surface vehicles (USVs). This paper improves the traditional D* Lite algorithm and achieves multi-goal path planning and collis...
Navigation is an indispensable component of ground and aerial mobile robots. Although there is a plethora of path planning algorithms, most of them generate paths that are not smooth and have angular turns. In many cases, it is not feasible for the r...
This paper presents a new approach for enhancing autonomous vehicle navigation and obstacle avoidance based on the integration of reinforcement learning with multiple sensors for navigation. The proposed system is designed to enable a reinforcement l...
Light Detection and Ranging (LiDAR) has become a benchmark sensing modality for autonomous unmanned aerial vehicle (UAV) navigation in GPS-denied and obstacle-dense environments such as forests, urban canyons, and indoor structures. This paper presen...
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