Feature extraction plays a crucial role in computer vision and autonomous navigation, offering valuable information for real-time localization and scene understanding. However, although multiple studies investigate keypoint detection and description...
Autonomous driving in unstructured environments is crucial for various applications, including agriculture, military, and mining. However, research in unstructured environments significantly lags behind that in structured environments, mainly due to...
The space environment is characterized by unstructured features, sparsity, and poor lighting conditions. The difficulty in extracting features from the visual frontend of traditional SLAM methods results in poor localization and time-consuming issues...
LiDAR-based semantic segmentation, particularly for unstructured environments, plays a crucial role in environment perception and driving decisions for unmanned ground vehicles. Unfortunately, chaotic unstructured environments, especially the high-pr...
As with the broad field of deep learning, autonomy is a research topic that has experienced a heavy explosion in attention from both the scientific and commercial industries due to its potential for the advancement of humanity in many cross-cutting d...
Inspired by the human 3D visual perception system, we present an obstacle detection and classification method based on the use of Time-of-Flight (ToF) cameras for robotic navigation in unstructured environments. The ToF camera provides 3D sensing by...
The capabilities of autonomous mobile robotic systems have been steadily improving due to recent advancements in computer science, engineering, and related disciplines such as cognitive science. In controlled environments, robots have achieved relati...
Accurate localization of robots in unstructured environments poses challenges due to low localization accuracy and local trajectory oscillation caused by complex feature points when using Euclidean-based filtering methods. In this study, we propose a...
This paper presents a focused investigation into real-time segmentation in unstructured environments, a crucial aspect for enabling autonomous navigation in off-road robots. To address this challenge, an improved variant of the DDRNet23-slim model is...
The identification of safflower filament targets and the precise localization of picking points are fundamental prerequisites for achieving automated filament retrieval. In light of challenges such as severe occlusion of targets, low recognition accu...
Path planning is a fundamental challenge for autonomous robots, particularly in unstructured environments, where issues such as low search efficiency, suboptimal path quality, and local optima often arise. To address these challenges and enable a non...
In mobile robotics, path planning enables autonomous navigation to specified destinations. However, complex terrain can lead to excessive tilting or even overturning, compromising stability and safety. Traditional path-planning algorithms often fail...
Autonomous navigation in GPS-denied, unstructured environments such as murky waters or complex seabeds remains a formidable challenge for robotic systems, primarily due to sensory degradation and the computational inefficiency of conventional algorit...
Autonomous navigation in cluttered and dynamic industrial environments remains a major challenge for mobile robots. Traditional occupancy-grid and geometric planning approaches often struggle in such unstructured settings due to partial observability...
The research and development of special robots such as excavation robots is an important way to achieve safe and efficient production in coal mines. Affected by the unstructured environment such as complex working conditions and unsteady factor distu...
Accurate obstacle detection plays a crucial role in the creation of high-precision maps within unstructured terrain environments, as it supplies vital decision-making information for unmanned engineering vehicles. Existing works primarily focus on th...
Autonomous legged navigation in unstructured environments is still an open problem which requires the ability of an intelligent agent to detect and react to potential obstacles found in its area. These obstacles may range from vehicles, pedestrians,...
This paper introduces GAUREAD, an end-to-end computer vision system that is able to autonomously read analogic gauges with circular shapes and linear scales in unstructured environments. Existing gauge reading software still relies on some manual ent...
Teleoperation is widely used for unmanned ground vehicle (UGV) navigation in military and civilian fields. However, the human operator has to limit speed to ensure the handling stability because of the low resolution of video, limited field of view a...
To ensure the safe production of mines, the intelligent trend of underground mining operations is gradually advancing. However, the operational environment of subterranean mining is intricate, making the conventional path-planning algorithm used by m...
The problem of autonomous navigation of a ground vehicle in unstructured environments is both challenging and crucial for the deployment of this type of vehicle in real-world applications. Several well-established communities in robotics research dea...
This article will present two swarming behaviors for deployment in unstructured environments using unmanned aerial vehicles (UAVs). These behaviors will use stigmergy for communication. We found that there are currently few realistic deployment appro...
Robot force control that needs to be customized for the robot structure in unstructured environments with difficult-to-tune parameters guarantees robots’ compliance and safe human–robot interaction in an increasingly expanding work enviro...
In the context of autonomous robots, one of the most important tasks is to prevent potential damage to the robot during navigation. For this purpose, it is often assumed that one must deal with known probabilistic obstacles, then compute the probabil...
Agricultural robots have demonstrated significant potential in enhancing farm operational efficiency and reducing manual labour. However, unstructured and complex farm environments present challenges to the precise localisation and navigation of robo...
This paper proposes an optimized trajectory planner and motion planner framework, which aim to deal with obstacle avoidance along a reference road for autonomous driving in unstructured environments. The trajectory planning problem is decomposed into...
This research work presents the design and the development of a cost-effective autonomous mobile robot for locating misplaced objects within unstructured indoor environments. The tools integrated into the proposed system for perception and localizati...
While mobile ground robots have now the physical capacity of travelling in unstructured challenging environments such as extraterrestrial surfaces or devastated terrains, their safe and efficient autonomous navigation has yet to be improved before en...
Autonomous harvesting and transportation is a long-term goal of the forest industry. One of the main challenges is the accurate localization of both vehicles and trees in a forest. Forests are unstructured environments where it is difficult to find a...
In this paper, the problem of vehicle guidance by means of an external leader is described. The objective is to navigate a four-wheeled vehicle through unstructured environments, characterized by the lack of availability of typical guidance infrastru...
In conventional point-line visual–inertial odometry systems in indoor environments, consideration of spatial position recovery and line feature classification can improve localization accuracy. In this paper, a monocular visual–inertial o...
Ground segmentation in LiDAR point clouds is a foundational capability for autonomous systems, enabling safe navigation in applications ranging from urban self-driving vehicles to planetary exploration rovers. Reliably distinguishing traversable surf...
Effective fruit identification and maturity detection are important for harvesting and managing tomatoes. Current deep learning detection algorithms typically demand significant computational resources and memory. Detecting severely stacked and obscu...
In the shipbuilding industry, welding automation using welding robots often relies on arc-sensing techniques due to spatial limitations. However, the reliability of the feedback current value, core sensing data, is reduced when welding target workpie...
Path planning aims to find a safe and efficient path from a starting point to an end point, and it has been well developed in fields such as robot navigation, autonomous driving, and intelligent decision systems. However, traditional path planning fa...
As industrial automation evolves towards human-centric, adaptable solutions, collaborative robots must overcome challenges in unstructured, dynamic environments. This paper extends our previous work on developing a digital shadow for industrial robot...
The intelligent transportation system, especially autonomous vehicles, has seen a lot of interest among researchers owing to the tremendous work in modern artificial intelligence (AI) techniques, especially deep neural learning. As a result of increa...
In a future intelligent factory, a robotic manipulator must work efficiently and safely in a Human–Robot collaborative and dynamic unstructured environment. Autonomous path planning is the most important issue which must be resolved first in the proc...
This paper investigates a path planning approach for the walking and obstacle avoidance of a blind hexapod robot in various field conditions. Hexapod robots often perform field tasks in unstructured environments, and their external sensors are affect...
Due to the uncertainty and complexity of the assembly process, the trajectory planning of a robot needs to consider the real-time obstacle avoidance problem when it completes the assembly in the unstructured workspace. To realize the safe assembly of...
Traditional monocular and stereo visual SLAM systems often fail to operate stably in complex unstructured environments (e.g., weakly textured or repetitively textured scenes) due to feature scarcity from their limited fields of view. In contrast, mul...
Recent advances in mobile robotics have emphasized the need for systems capable of operating in unstructured environments, combining obstacle negotiation, stability, and adaptability. This study presents the preliminary design and testing of Brush.Q,...
One of the most relevant problems related to Unmanned Aerial Vehicle’s (UAV) autonomous navigation for industrial inspection is localization or pose estimation relative to significant elements of the environment. This paper analyzes two differe...
This paper presents a fast and robust approach for estimating the flight altitude of multirotor Unmanned Aerial Vehicles (UAVs) using 3D point cloud sensors in cluttered, unstructured, and dynamic indoor environments. The objective is to present a fl...
The application of intelligent equipment and technologies such as robots and unmanned vehicles is an important part of the construction of intelligent mines, and has become China’s national coal energy development strategy and the consensus of...
Addressing key challenges in unstructured environments, including local optimum traps, limited real-time interaction, and convergence difficulties, this research pioneers a hybrid reinforcement learning approach that combines simulated annealing (SA)...
Workpiece location is critical to efficiently plan actions downstream in manufacturing processes. In labor-intensive heavy industries, like construction and shipbuilding, multiple stakeholders interact, stack and move workpieces in the absence of any...
Indoor Positioning Systems (IPSs) for emergency responders is a challenging field attracting researchers worldwide. When compared with traditional indoor positioning solutions, the IPSs for emergency responders stand out as they have to operate in ha...
Unmanned articulated vehicles play a crucial role in the intelligent mine system and have been extensively investigated and implemented in the fields of mine transportation, agriculture and forestry construction. However, the working environment of a...
Logging and tracking raw materials, workpieces and engineered products for seamless and quick pulls is a complex task in the construction and shipbuilding industries due to lack of structured storage solutions. Additional uncertainty is introduced if...
of 12