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Topic Review
Anomaly Detection in Autonomous Robotic Missions
An anomaly in autonomous robotic missions (ARM) is a deviation from the expected behaviour, performance, or state of the robotic system and its environment, which may impact the mission’s objectives, safety, or efficiency; and this anomaly can be caused either by system faults or the change in the environmental dynamics of interaction. The nuanced understanding of anomaly categories facilitates a more strategic approach, ensuring that detection methods are more effective in addressing the specific nature of the anomaly.
  • 304
  • 11 Mar 2024
Topic Review
Reducing Oscillations for Obstacle Avoidance in Dense Environment
Due to their high flexibility, quadrotor unmanned aerial vehicles (QUAVs) have gained significant popularity in various applications, including parcel delivery, precision agriculture, search and rescue, and surveillance. In these scenarios, the QUAV is typically required to autonomously navigate to a target position.
  • 62
  • 07 Mar 2024
Topic Review
Robotic Applications in Maintenance, Repair, and Overhaul Hangar
The aerospace industry has continually evolved to guarantee the safety and reliability of aircraft to make air travel one of the safest and most reliable means of transportation. Mobile robots encompass comprehensive system structures that work together through perception, detection, motion planning, and control. The subject of autonomous robot navigation entails mapping, localisation, obstacle detection, avoidance, and achieving an optimal path from a starting point to a predefined target location efficiently.
  • 55
  • 06 Mar 2024
Topic Review
Human Decision Making in Human–Robot Collaboration
The advent of Industry 4.0 has heralded advancements in human–robot collaboration (HRC), necessitating a deeper understanding of the factors influencing human decision making within this domain. An HRC system combines human soft skills such as decision making, intelligence, problem-solving, adaptability and flexibility with robots’ precision, repeatability, and the ability to work in dangerous environments.
  • 167
  • 22 Feb 2024
Topic Review
Action Recognition for Human–Robot Teaming
Human–robot teaming (HrT) is being adopted in an increasing range of industries and work environments. Effective HrT relies on the success of complex and dynamic human–robot interaction. Although it may be optimal for robots to possess all the social and emotional skills to function as productive team members, certain cognitive capabilities can enable them to develop attitude-based competencies for optimizing teams. Despite the extensive research into the human–human team structure, the domain of HrT research remains relatively limited. In this sense, incorporating established human–human teaming (HhT) elements may prove practical.
  • 85
  • 01 Feb 2024
Topic Review
Swarm Robotics for Area Coverage Problem
The area coverage problem solution is one of the vital research areas which can benefit from swarm robotics. The greatest challenge to the swarm robotics system is to complete the task of covering an area effectively. Many domains where area coverage is essential include exploration, surveillance, mapping, foraging, and several other applications.
  • 128
  • 19 Jan 2024
Topic Review
Robot Task Modeling and Notation 2.0
RTMN 2.0, an extension of the modeling language RTMN. RTMN combines process modeling and robot execution. Intuitive robot programming allows those without programming expertise to plan and control robots through easily understandable predefined modeling notations. These notations achieve no-code programming and serve as templates for users to create their processes via drag-and-drop functions with graphical representations.
  • 98
  • 15 Jan 2024
Topic Review
LiDAR Local Domain Adaptation for Autonomous Vehicles
Perception algorithms for autonomous vehicles demand large, labeled datasets. Real-world data acquisition and annotation costs are high, making synthetic data from simulation a cost-effective option. However, training on one source domain and testing on a target domain can cause a domain shift attributed to local structure differences, resulting in a decrease in the model’s performance. Domain adaptation is a form of transfer learning that aims to minimize the domain shift between datasets.
  • 147
  • 05 Jan 2024
Topic Review
Spatial and Temporal Human Action Recognition Analysis
Human action recognition in computer vision is the task that identifies how a person or a group acts on a video sequence. Early methods that rely on representation-based solutions, like the histogram of oriented gradients (HOG), local binary patterns (LBP), and motion analysis, have been used to address this problem over the years. Later works are based on machine and deep-learning techniques, such as support vector machines (SVM), two- or three-dimensional convolutional neural networks (2D-CNNs, 3D-CNNs), recurrent neural networks (RNNs), and vision transformers (ViT), aiming to enhance the performance and reduce bias.
  • 88
  • 22 Dec 2023
Topic Review
Automatic Navigation Approaches for Flying Robots
Various approaches to achieve autonomous flight have been proposed in the literature, which can be broadly categorized into the following three types: (1) Trajectory-based optimization methods: These methods involve designing a set of optimal trajectories that the robot should follow to reach its destination; (2) Imitation-learning-based methods; (3) Reinforcement-learning-based methods.
  • 95
  • 18 Dec 2023
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