Articles tagged with Human Robot Interaction
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Researchers at Harvard University have developed a new design method for optimizing rolling contact joints in robots, which can lead to better grippers, assistive devices, and more efficient robotic movement. The optimized joints performed spectacularly, correcting misalignment by 99% in knee-assist devices.
A new robotic design uses vine-like structures to lift and grasp a variety of objects, including humans, with a gentler approach. The robot can snake around obstacles, squeeze through tight spaces, and even secure itself in a closed loop to create a sling.
A breakthrough AI system called OmniPredict can predict human pedestrian behaviors with unprecedented accuracy, revolutionizing self-driving cars and urban mobility. The model combines visual cues with contextual information to anticipate pedestrians' next moves, reducing the risk of accidents and improving traffic safety.
In a study by SWPS University, researchers found that children interact with polite robots almost always respond politely. Younger children and girls are more likely to anthropomorphise the robot, suggesting social cues in interactions between children and robots are crucial for positive learning outcomes.
A recent study reveals that the response to witnessing robot mistreatment depends on factors such as the robot's humanlike design and the observer's moral identity. Anthropomorphism influences empathy, encouraging customers to treat robots with dignity, while moral identity plays a crucial role in shaping behavioral contagion.
A team of researchers at the University of Bath has developed a new technology called HydroHaptics that allows users to interact with soft objects in a meaningful way. The system uses a deformable surface to provide tactile feedback, enabling applications such as wearable tech, gaming, and medical simulation.
The International Telecommunication Union (ITU) has launched an initiative to bring artificial intelligence and robotics training to students across Africa. The programme combines hands-on AI and robotics training for young people in underserved communities, with a focus on reaching girls and other underrepresented groups.
Researchers discovered that humans treat a robotic hand as part of their body schema when working together on tasks, particularly when the robot's gestures are synchronized with those of humans. The study paves the way for better-designed robots that can interact more intuitively with humans.
A new study from the University of Chicago found that children experience less anxiety when reading aloud to a robot than to a human adult. The robot's calming influence helped children feel more comfortable making mistakes, creating a more encouraging environment for building their reading skills. While there were no substantial diffe...
Researchers developed algorithms that enable robots to create the best possible outcomes from their actions while minimizing uncertainty and risk. The new strategies allow robots to anticipate human actions, adapt to different scenarios, and prioritize human safety.
Computer scientists at Princeton University are working on a system that pairs virtual reality with a physical robot, allowing users to seamlessly interact with the physical world. The technology enables tasks like selecting an object across the room or erasing physical objects from view, creating a more immersive experience.
A wearable robot has been upgraded to provide personalized assistance to ALS and stroke patients. The device uses machine learning and a physics-based model to adapt to an individual user's movements, offering more nuanced help with daily tasks.
A study found that social robots like Luka can become deeply embedded in families over time, taking on emotional and symbolic roles. Children often reinterpret their relationship with the robot as they grow older, repurposing it as a companion or keepsake.
Researchers at TUM create standardized procedure to compare industrial robots and assess their sensitivity, categorizing them into 'industrial robots,' 'cobots,' 'soft robots' and 'tactile robots.' This evaluation scheme has the potential to become an industrial testing standard, creating a seal of quality for the robotics market.
A new type of intrinsically soft robotic sensors with quadruple sensing functionalities has been developed, enabling the perception of complex environments in both contact and non-contact manners. The sensors can be fully recycled for reuse, achieving superior cost-efficiency and eco-sustainability.
A team of undergrads at CU Boulder has created a digital twin for their robot, Armstrong, which is being used to train human operators on how to navigate the moon's surface. The study found that training in a digital environment resulted in faster task completion and reduced stress.
The AI for Good Global Summit 2025 will showcase AI innovations delivering better healthcare and education, reducing disaster risks, ensuring water and food security, and bolstering economic resilience. The event, organized by the International Telecommunication Union (ITU), features talks from AI leaders and 100+ demos.
Scientists created a low-cost, durable, highly-sensitive robotic 'skin' that can detect various types of touch and pressure. The technology senses multiple physical inputs simultaneously, allowing robots to interact with their environment in a more human-like way.
The research team developed a novel auditory technology that allows sound-based interaction between humans and robots, even in noisy environments. The technology facilitates sound-based recognition of human positions using only a single microphone.
The Association for Computing Machinery has recognized five individuals with awards for their impactful service to the computing field. Manish Parashar received the ACM Distinguished Service Award for his leadership in furthering the transformative impact of computer science on science and engineering.
Researchers developed T2IRay, a VR input method with precise object pointing, and ChoreoCraft, a virtual reality tool supporting choreographers' creativity. These technologies received Honorable Mention awards at CHI 2025 for their contributions to human-computer interaction.
A robotic hand developed at EPFL can pick up 24 different objects with human-like movements that emerge spontaneously due to compliant materials and structures. The device uses 'self-organized' grasps that mimic natural human grips with a high success rate, making it suitable for highly unpredictable environments.
A team of Brown University researchers has developed an artificial intelligence model called MotionGlot that can generate movement in robots and animated figures. The model enables users to type an action and generates accurate representations of that motion, translating across different robot and figure types.
Researchers found that service robots with male characteristics can be more persuasive when interacting with women who have a low sense of power. Conversely, cute features in robot design can reduce the effect of portrayed gender on persuasiveness, making them effective for both male and female customers.
Kavraki's interdisciplinary research in robotics and biomedicine has been recognized for its impact on manufacturing, space exploration, and medicine. Her work bridges theory and application, with contributions to novel robot motion planning, personalized cancer treatments, and drug discovery.
Computer scientists at the University of Bath reprogrammed a Roomba to perform four new tasks, showcasing the untapped potential of domestic robots. The researchers identified over 100 ways to tap into the latent potential of robotic devices, proposing functions such as playing with pets, watering plants, and delivering breakfast in bed.
A new robotic system uses cues in a scene to determine a human's objective and quickly identify relevant objects, enabling intuitive assistance in household, workplace, and warehouse settings. The approach achieved 90% accuracy in predicting human objectives and 96% accuracy in identifying relevant objects.
Researchers found that realistic AI avatars are rated more positively than cartoon-style ones for perceived competence, integrity, and benevolence. However, individual factors such as prior AI knowledge and trust in science moderate perceptions of trustworthiness.
The robot can switch between physical space and cyberspace modes using bioelectrical signals and gaze information, managing arm hand systems and IoT devices with high success rate. This technology aims to reduce nursing care costs and medical expenses by enhancing independence.
Researchers developed a lighter, smarter magnetoreceptive e-skin that tracks signal paths for applications like virtual reality and robotic systems. The new technology emulates the functioning of real skin and saves energy by using a single global sensor surface and central processing unit.
A study from Reichman University's School of Communications found that a robotic dog can influence leadership dynamics between humans by displaying clear preferences for team members. This can lead to spontaneous emergence of leadership, with the favored participant taking charge without explicit guidance.
Researchers found that people demonstrate a significant level of obedience towards humanoid robots, but it is slightly lower than towards humans. The study also showed that work efficiency under robot supervision is lower, with participants completing tasks more slowly and less effectively.
A new framework allows users to correct a robot's actions in real-time using intuitive interactions, such as pointing or nudging the arm. The method achieves a success rate of 21% higher than an alternative approach, enabling more efficient and accurate task completion.
Johns Hopkins engineers developed a pioneering prosthetic hand that can grip and grasp everyday objects like a human, using a hybrid design that combines rigid and soft robotics. The system achieves 99.69% accuracy in handling objects of varying textures and materials.
Researchers at UC3M developed a new soft joint model that enables versatility of movement, adaptability, and safety in robots. The asymmetrical triangular structure allows for greater bending angles with less force, providing operational protection and increased safety in human-robot interactions.
Researchers are developing a software framework for crowd-sourced 3D map generation and visual localization from camera data to improve real-time updates and low-cost visual localization. This technology aims to advance self-driving vehicles and enable fully automated transportation
Researchers developed a robot that mimics the bunting motion of a cat rubbing its head against a person, which has been shown to have a healing effect on humans. The robot's variable stiffness mechanism was found to be most effective in reducing tension among participants.
The Cambridge Handbook of the Law, Policy, and Regulation for Human-Robot Interaction addresses emerging issues in AI and robots, including privacy, safety, and regulation. The book offers valuable insights into ethical dilemmas and proposes solutions to balance enforceability and flexibility.
A study published in Science Robotics found that diverse and inclusive teams in robotics research achieve higher motivation, commitment, and productivity. The team identified seven main benefits of workforce diversity and inclusive leadership, including increased innovation and reduced bias.
Researchers created a measurement scale to assess robot human likeness, revealing four key qualities: appearance, emotional capacity, social intelligence, and self-understanding. To seem lifelike, robots must exhibit these traits, with self-understanding being the most challenging aspect to simulate.
The NUS research team has developed flexible fibres with self-healing, light-emitting and magnetic properties. The Scalable Hydrogel-clad Ionotronic Nickel-core Electroluminescent (SHINE) fibre offers a more efficient, durable and versatile alternative to existing light-emitting fibres.
Researchers developed a platform to help AI learn complex tasks through nuance and real-time instruction, achieving up to a 30% increase in success rates. The GUIDE framework allows humans to provide ongoing, nuanced feedback, fostering incremental improvements and deeper understanding.
Researchers discovered that synchronized movement between humans and robots builds trust, which can improve the success of human-robot teams. The study found that users who reported lower trust in the robots mirrored their movements less, suggesting that co-movement could be used to detect problems with user trust.
A review paper explores how robots can aid in understanding the human sense of self, including simulating mind and brain processes and testing social capacities. Researchers aim to transfer some features of human self-awareness to robots, which could provide insights into its development and potential applications.
Researchers developed a multimodal dataset, TimelyTale, to gather passenger-specific sensor data for context-relevant explanations. The approach effectively identified the timing and frequency of passenger demands for explanations, enabling the creation of a machine-learning model to predict the best time for providing an explanation.
Researchers used a virtual cow game to study human movement and navigation, developing a model that can simulate human behavior and predict choices. The study found that humans make decisions based on angular distance and previous choices, and the developed model could accurately mimic these patterns.
A new system dubbed SonicSense allows robots to interpret the world through acoustic vibrations, giving them a richer ability to 'feel' and understand objects. The system, featuring a robotic hand with contact microphones, can identify materials, shapes, and recognize objects in complex environments.
A new knee exoskeleton has been developed to support the quadriceps muscles during lifting tasks, helping workers maintain better posture even when fatigued. The device, which uses a complex algorithm to predict assistance needs, enabled participants to lift faster and with improved posture.
A study of 498 participants found that humans disapprove of hidden state deceptions but approve of external state deceptions that protect someone's feelings. The researchers suggest regulation to protect users from harmful deceptions and recommend further experimentation with real-life reactions.
The Human AugmentatioN via Dexterity (HAND) center aims to develop robots capable of enhancing human labor through engineered systems of dexterous robotic hands, AI-powered fine motor skills, and human interface. The center's goal is to make robotic assistance accessible and applicable to a wide range of physical actions.
Researchers will create versatile and easy-to-integrate robots capable of intelligent grasping, fine motor skills, and hand-eye coordination. The goal is to empower diverse workforces with robotic solutions, improving worker productivity and job opportunities.
A new algorithm developed at Washington State University improves safety and efficiency in robots working with humans by accounting for human carelessness. The tool has shown a maximum improvement of 80% in safety and 38% in efficiency compared to existing methods, and the researchers plan to test it in real-world settings.
Researchers have created a novel system called ConTac, which can estimate the shape and contact of a robotic arm with soft skin using a single sensing module. The system consists of a backbone, soft skin with markers, a camera to observe skin deformation, and models for shape and contact sensing.
Researchers found that socially assistive robots improved stroke rehabilitation outcomes by encouraging people to continue their treatment in a non-judgmental setting. Participants who used the robots showed significant improvements in kinematic and clinical measures, including smoothness of movement and upper-extremity assessments.
A team of researchers is creating a socially assistive model for a robotic dog that adapts its behavior based on the owner's physiological and emotional characteristics. The project aims to improve interactions between humans and robots in home and healthcare settings.
A humanoid robot has been trained to learn and perform various expressive movements, including simple dance routines and gestures. The enhanced expressiveness and agility of the robot pave the way for improving human-robot interactions in settings such as factory assembly lines, hospitals, and homes.
The ZEN-MRI project, funded by the German Ministry of Education and Research, aims to achieve a congenial co-existence between human beings and robots in public areas. Researchers will investigate how to design robots that are perceived as unthreatening and sympathetic.
The University of Maryland team created a camera mechanism that mimics the involuntary movements of the human eye, resulting in sharper and more accurate images. The Artificial Microsaccade-Enhanced Event Camera (AMI-EV) has implications for robotics, national defense, and industries relying on accurate image capture.
Researchers found that humans feel jointly a sense of agency with humanoid robots when they perceive them as intentional and social agents. This teamwork is more likely to occur when the robot displays human-like behavior and emotions.
Scientists at UVA and Toyota Research Institute create language representations of driving behavior to enable robots to associate words with environmental interactions. This allows cars to provide guidance and adjust speed in challenging situations, improving safety and usability.