Results for "Manipulation"

17 articles found

Dozens of nudify apps found on Google and Apple's app stores

The Tech Transparency Project identified 55 apps on Google Play Store and 48 on Apple's App Store capable of creating nonconsensual sexualized deepfakes, which have been downloaded over 705 million times and generated $117 million in revenue. The report highlights the broader issue of AI image manipulation tools evading app store moderation, following similar findings in 2024 and amid ongoing scrutiny of xAI's Grok for generating millions of non-consensual sexualized images.

The Verge AI1/27/2026

Robotiq brings sense of touch to physical AI with fingertips for 2F grippers

Robotiq launched the TSF-85 tactile sensor fingertips for its 2F-85 Adaptive Gripper, enabling robots to sense and manipulate objects through touch using capacitor-based sensing technology. The product combines adaptive gripping with high-frequency tactile sensing (1000 Hz micro-slip detection) and is based on academic research from École de technologie supérieure, aiming to give industrial robots better perception and manipulation capabilities at scale.

Robotics Business Review1/27/2026

Thomas Pilz on innovation and safety in robotics

This Robot Report Podcast episode features Thomas Pilz from Pilz GmbH discussing innovation and safety in robotics, alongside coverage of major industry news including iRobot's emergence from bankruptcy under new ownership, Serve Robotics' acquisition of hospital logistics provider Diligent Robotics, and Microsoft Research's announcement of Rho-alpha, a vision-language-action model for robotic manipulation tasks. The episode explores current challenges in the rapidly evolving robotics landscape and emerging technologies shaping the industry.

The Robot Report1/23/2026

Microsoft Research reveals Rho-alpha vision-language-action model for robots

Microsoft Research announced Rho-alpha (ρα), a vision-language-action model derived from its Phi series that enables robots to perceive, reason, and act autonomously by integrating tactile sensing and learning from human feedback. The model translates natural language commands into control signals for bimanual manipulation tasks and is being evaluated on dual-arm cobots and humanoid robots, with training enhanced through simulation, physical demonstrations, and reinforcement learning.

The Robot Report1/21/2026

Soft robotic hand 'sees' around corners to achieve human-like touch

Researchers at Zhejiang University developed FlexiRay, a soft robotic hand that combines a flexible bio-inspired structure with deep learning algorithms to achieve human-like tactile sensing capabilities. The key innovation is an internal multi-mirror optical system that maintains camera vision even when the soft finger is significantly deformed, allowing the robot to reliably manipulate fragile and irregularly shaped objects by analyzing deformation patterns.

Phys.org Robotics1/17/2026

Serve Robotics to acquire hospital logistics provider Diligent Robotics

Serve Robotics is acquiring hospital logistics provider Diligent Robotics for $29 million, gaining access to Moxi, a mobile manipulation robot currently operating in over 25 hospitals. The acquisition marks Serve's entry into indoor environments and healthcare, while combining Serve's outdoor autonomous fleet expertise with Diligent's mobile manipulation capabilities and real-world deployment experience.

The Robot Report1/20/2026

ChatGPT falls to new data-pilfering attack as a vicious cycle in AI continues

Researchers at Radware discovered ZombieAgent, a new data-exfiltration vulnerability in ChatGPT that bypasses previous security mitigations for the ShadowLeak attack by using character-by-character exfiltration and indirect link manipulation. The attack highlights a fundamental challenge in AI security: LLMs cannot reliably distinguish between legitimate user instructions and malicious directives embedded in external content, forcing vendors to deploy reactive guardrails rather than addressing the underlying class of prompt injection vulnerabilities.

Ars Technica1/8/2026

Robotic arm successfully learns 1,000 manipulation tasks in one day

Researchers at Imperial College London developed a new imitation learning approach that enabled a robotic arm to successfully learn 1,000 different manipulation tasks in a single day. The method, published in Science Robotics, uses trajectory decomposition and retrieval-based generalization to allow robots to learn multiple tasks efficiently with minimal training data, challenging the assumption that capable robotic systems require massive datasets and complex models.

Phys.org Robotics12/17/2025

Ghost Robotics' Arm Brings Manipulation to Military Quadrupeds

Ghost Robotics has added a manipulator arm to its Vision 60 quadruped robot, enabling it to lift up to 3.75 kilograms while maintaining the platform's waterproof capabilities up to 1 meter depth. The development reflects growing competition in legged robotics, particularly from Chinese manufacturers, driving innovation in military and industrial applications.

IEEE Spectrum Robotics12/11/2025

The science of human touch, and why it's so hard to replicate in robots

This article explores the scientific challenges of replicating human tactile sensation in robots, examining why touch perception remains far more difficult to implement than vision despite advances in robotic sight and manipulation. The piece discusses the complexity of translating human sensory feedback into robotic systems capable of handling delicate tasks.

Phys.org Robotics12/10/2025

Generations in Dialogue: Embodied AI, robotics, perception, and action with Professor Roberto Martín-Martín

This podcast episode features Professor Roberto Martín-Martín from the University of Texas at Austin discussing his research in embodied AI, robotics, computer vision, and machine learning for autonomous agents. The conversation explores how robots can perceive, learn, and act in the real world, covering topics from manipulation tasks to mobile robotics and human-robot interaction.

Robohub12/8/2025

Teaching robot policies without new demonstrations: interview with Jiahui Zhang and Jesse Zhang

Researchers introduce ReWiND, a framework that enables robot manipulation policies to learn new language-conditioned tasks without requiring per-task demonstrations. The method uses a three-stage approach: learning a reward function from minimal demonstrations, pre-training a policy with offline RL, and fine-tuning on new tasks using the learned reward function as feedback, with a novel video rewind augmentation to simulate failed behaviors.

Robohub12/4/2025

Video Friday: Watch Robots Throw, Catch, and Hit a Baseball

A compilation of robot demonstration videos showcasing various athletic capabilities, including robots that can throw, catch, and hit a baseball. The video collection highlights recent robotics research and development in dynamic motion control and object manipulation tasks.

IEEE Spectrum Robotics11/21/2025

Why Is Everyone's Robot Folding Clothes?

The article explores why multiple robotics companies are focusing on cloth folding as a benchmark task for humanoid robots, examining what this reveals about advances in robot learning and manipulation. Chris Paxton from Agility Robotics discusses the technical significance of clothing manipulation as a test case for modern AI-driven robotic systems, including Figure's humanoid robot.

IEEE Spectrum Robotics11/19/2025