Embodied perception Latest coverage

CMU Researchers Give Robots a Delicate Touch

Carnegie Mellon University researchers have developed a robotic fingertip that enables robots to handle delicate tasks, such as picking up fragile or tiny objects like pills and potato chips. The fingertip, which attaches to the DeltaHands device, uses a strain gauge and contact microphone to measure pressure and capture microvibrations, allowing the robot to sense and manipulate objects with greater precision. The low-cost, 3D-printable design offers versatility for a range of tasks, from counting paper cups to identifying material compositions through vibrations. The work was presented at the 2026 Intelligent Robots and Systems Conference.

Can Embodied Intelligence Be Trusted? Sergey Levine Points the Way

At the 2026 World Robotics Conference, Sergey Levine pointed out that the robotics industry is undergoing a shift from controlling the body to developing decision-making capabilities. He emphasized that robots need to combine prior knowledge with real-world experience to achieve true intelligence. Although robots are still in the foundational technology stage, through data flywheels and scaling, they may eventually enable broader applications.

Guidelines for Building an Embodied Intelligence Lab at the University: From Hardware Selection to Data Closed-Loop

This guide addresses the challenges of building a functional embodied intelligence lab in academia, emphasizing the importance of data pipelines over hardware procurement. It covers hardware selection, sensor configuration, data collection, simulation platforms, and software architecture, offering practical advice for avoiding common pitfalls in lab setup and operation.

CoRL 2026｜Making Robots More Agile: Starting with Learning to Walk

This paper presents LeaP, a learnable source prior for generative robot policies, which replaces fixed standard Gaussian distributions with state-dependent random initialization. LeaP jointly learns the mean and variance of an initial Gaussian distribution, improving action generation in robotic tasks. The method achieves an average success rate of 81.6% in simulation and 80.0% on real robotic arms, outperforming existing baselines like A2A and VITA. The paper is accepted at CoRL 2026, and the code is open-sourced.

New robot falls like a maple seed then sails like a boat once it hits water

Researchers at Singapore University of Technology and Design (SUTD) have developed ALBATROSS, a nature-inspired robotic platform that falls like a maple seed during its autorotating descent and then sails autonomously on water using wind energy. The system uses rigid wingsails for both slowing its fall and powering its movement, enabling it to reach remote waters quickly and monitor environmental conditions for extended periods.

Robot Hands for Modern AI and Real Work

Boston Dynamics announces a new hand for its Atlas robot, designed for dexterous manipulation and real-world tasks. The hand features 13 degrees of freedom, direct actuation, and is optimized for simulation and reinforcement learning. It avoids a pinky finger to balance complexity and functionality, enabling tasks like tool use and object reorientation.

Motors Don't Need Upgrades, Robots Can Run Faster. Beihang University Science Subjournal Reveals New Logic for Quadruped Locomotion

Professor Shi Qing's team from Beijing Institute of Technology was inspired by the high-speed running mechanism of the elephant shrew. They designed a micro quadruped robot named FLEXOR equipped with a dual-joint coupled spine. Through dynamic spine-leg coordination, the robot achieved a 31.6% increase in speed and a 32.2% reduction in energy consumption without upgrading its motors. The study reveals the critical role of the timing coordination between the spine and legs in locomotion performance and verifies the universality of this mechanism across different robot morphologies, providing new insights for highly mobile embodied intelligent robots.

A continuous artificial muscle unlocks dexterous soft-robot motion

Researchers from the National University of Singapore have developed a continuous artificial muscle inspired by the neuromuscular control of an octopus. This design allows for precise, localized control of soft robotic arms without the need for multiple actuators. The system enables compact, lightweight robotic arms capable of complex movements and tasks such as sampling and object retrieval. The approach could have applications in confined spaces, aerial deployment, and industrial settings.

Soccer-playing humanoid robots score a major robotics goal for coordination

Researchers at Tsinghua University have developed a new control system for humanoid robots that enables coordinated soccer-playing behavior using onboard vision. The system was tested on a real robot and achieved an 80-90% success rate in scoring goals from the front half of the field, with a 64% reduction in response time compared to a rule-based system. The study was published in Science Robotics and demonstrates a significant advancement in embodied AI and robot coordination.

GPT-6 Astra Connects to Unitree G1, Cleans the Kitchen

The Stanford team's HomeBody project demonstrates how GPT-6 Astra controls the Unitree G1 robot to complete kitchen cleaning tasks through a three-step process: spatial exploration, digital twin simulation, and task execution. The system uses pre-trained models and a skill library to perform complex operations in new environments without additional training.

Deployment Year Begins: AGIBOT Deploys 100 Robots in Retail Stores

AGIBOT Robotics has deployed 100 units of the Lingxi X2 humanoid robot in 100 retail stores of Aishida, achieving a 39% increase in store sales. The robots, named 'Aibao,' engage customers by understanding their cooking needs and guiding them toward suitable products, while also seamlessly transferring conversations to human staff when necessary. This marks a milestone in the deployment of embodied AI in real-world retail environments.

Powered by muscle cells, a paper-thin robot swims through a watery maze

MIT engineers have developed a soft, paper-thin robot that swims through water using a single layer of genetically engineered muscle cells. The robot's 'fins' are covered with live muscle cells that twitch in response to light, allowing it to flap and navigate through a watery maze. The study demonstrates the potential of biohybrid robots for delicate aquatic tasks, with the robot achieving a swimming speed of about four times its body length per minute.

Robotics Roadmaps from Around the World: Spotlight of the Month - China

China is pursuing a strategic roadmap through its Five-Year Plans to dominate the global robotics industry, focusing on embodied AI and humanoid robotics. The 13th and 14th FYPs laid the foundation for industrial automation, while the 15th FYP emphasizes embodied intelligence, with state support for R&D and mass deployment of humanoids. Despite achievements in market share and production scale, challenges remain in precision hardware and semiconductor self-sufficiency, with risks of overcapacity and market volatility.

NVIDIA Isaac ROS 5.0 Advances Agentic, Open Source Robotics Development

NVIDIA Isaac ROS 5.0, released at ROSCon 2026, enhances open source robotics development with agentic workflows, GPU acceleration, and new skills for perception and manipulation. It supports ROS Lyrical and Ubuntu 24.04, enabling developers to build and deploy high-performance robotics applications using NVIDIA's accelerated computing and AI models.

Robotic lab sets up and runs optics experiments on demand

MIT researchers have developed a reconfigurable robotic lab that autonomously assembles, tunes, and dismantles optical experiments. The system uses robotic arms, 3D-printed component housings, and a cloud-based interface to enable remote operation. It can build and fine-tune a laser cavity in under 30 minutes, demonstrating the potential for fully automated optical experiments.

Skeleton-guided geometry-aware auto-labeling for robotic grasping: From 4-DoF learning to 6-DoF execution

This research introduces a novel algorithm for generating grasp keypoints using straight skeletons to identify high-potential regions for stable grasping. A fully automated pipeline enables large-scale annotation without human intervention, and a new architecture, SkelGG-CNN, is introduced for 4-DoF grasping. The method is extended to 6-DoF grasping using a generalized quasi-3D skeletonization algorithm, achieving high accuracy on multiple benchmarks and real-world experiments. The framework enables efficient training of lightweight models for real-world deployment.

Robotic help in high-risk twin pregnancies

Researchers at ETH Zurich have developed a robotic platform with a magnetically controllable endoscope to improve the safety and precision of fetal surgery for twin pregnancies with shared placentas. The system uses magnetic fields to bend the endoscope, enabling better access to blood vessels, and combines panoramic imaging with real-time navigation. The technology has been tested in an animal model and is now being refined for human clinical use.

Unitree@UnitreeRobotics· 09:01SignalEditorial score6868

Unitree has fully open-sourced its UnifoLM-WLA-1.0 embodied foundation model, achieving new state-of-the-art results across multiple benchmarks. The model supports cross-task and cross-end-effector generalization, enabling whole-body coordination for both desktop and mobile manipulation.

This Robot Will Draw Your Blood Now

Aletta, the first autonomous blood-draw device approved for use in the U.S., uses imaging and robotics to perform blood draws with high success rates, even in challenging cases. While it addresses staffing shortages in clinical labs, concerns about skin tone bias and sample quality persist, requiring further validation.

Researchers tune into Arctic under-ice sounds and test through-ice communication

Researchers from MIT Lincoln Laboratory deployed sensors in the Arctic to monitor under-ice sounds and test through-ice communication using a magnetic modem. The study addresses challenges in extreme weather and highlights the importance of community collaboration and sensor deployment strategies for Arctic research.