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Topic Review
Robot Arm Reaching Based on Inner Rehearsal
Robot arm motion control is a fundamental aspect of robot capabilities, with arm reaching ability serving as the foundation for complex arm manipulation tasks. The researchers propose a robot arm motion control method based on inner rehearsal. Inspired by the cognitive mechanism of inner rehearsal observed in humans, this approach allows the robot to predict or evaluate the outcomes of motion commands before execution. By enhancing the learning efficiency of models and reducing excessive physical executions, the method aims to improve robot arm reaching across different platforms.
  • 619
  • 08 Nov 2023
Topic Review
Robot-Assisted Therapy for Autistic Children
Children with autism face a range of challenges when it comes to verbal and nonverbal communication. It is essential that children participate in a variety of social, educational, and therapeutic activities to acquire knowledge that is essential for cognitive and social development. The robot can engage these children in ways that demonstrate and train essential aspects of human interaction, guiding them in therapeutic sessions to practice more complex forms of interaction found in social human-to-human interactions.
  • 607
  • 09 Aug 2023
Topic Review
Risk Determination versus Risk Perception
Researchers review the progress in developing a science of interdependence applied to the determinations and perceptions of risk for autonomous human–machine systems based on a case study of the Department of Defense’s (DoD) faulty determination of risk in a drone strike in Afghanistan; the DoD’s assessment was rushed, suppressing alternative risk perceptions.
  • 599
  • 21 Jun 2023
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.
  • 594
  • 05 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.
  • 586
  • 15 Jan 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.
  • 571
  • 07 Mar 2024
Topic Review
Intelligent Drone Swarms in Post-Disaster Areas
Drone Swarms Routing Problem (DSRP), which consists of identifying the maximum number of victims in post-disaster areas. The post-disaster area is modeled in a complete graph, where each search location is represented by a vertex, and the edges are the shortest paths between destinations, with an associated weight, corresponding to the battery consumption to fly to a location. In addition, in the DSRP addressed here, a set of drones are deployed in a cooperative drone swarms approach to boost the search. In this context, a V-shaped formation is applied with leader replacements, which allows energy saving.
  • 563
  • 07 Dec 2023
Topic Review
Recognition of Grasping Patterns for Human–Robot Collaboration
Recent advances in the field of collaborative robotics aim to endow industrial robots with prediction and anticipation abilities. In many shared tasks, the robot’s ability to accurately perceive and recognize the objects being manipulated by the human operator is crucial to make predictions about the operator’s intentions.
  • 538
  • 16 Nov 2023
Topic Review
Deformable Object Manipulation in Caregiving Scenarios
The growing importance of deformable object manipulation (DOM) in caregiving settings can be attributed to various factors. One significant driving force is the aging population, which has led to increasing demand for caregiving services. In addition to supporting the elderly, deformable object manipulation technologies can assist individuals with disabilities and special needs, improving their quality of life and promoting independence. Another essential aspect of deformable object manipulation in caregiving scenarios is the potential to enhance precision and safety in medical procedures. These technologies can reduce the physical strain experienced by human caregivers, preventing injuries and enabling them to provide better patient care.
  • 525
  • 17 Nov 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.
  • 524
  • 18 Dec 2023
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.
  • 507
  • 22 Dec 2023
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.
  • 393
  • 01 Feb 2024
Topic Review
Social Exclusion in Human-Robot Interaction
As the technology for social robots is maturing at a rapid rate, one expects that scenarios for human–robot teams, which so far have remained in the realm of fiction (for example, The Murderbot Diaries by Martha Wells), will become a reality soon. Philosophers are discussing ways to redefine the concept of friendship to include robots as well. To prepare for this inevitable future, it is necessary that we study cognitive and affective aspects of how humans respond to robot team members.
  • 353
  • 17 Nov 2023
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