Technology areas
Grasping and manipulation
Grasping, dexterous hand manipulation, dual-arm coordination, assembly, contact-rich manipulation, deformable objects, tool use, and mobile manipulation. The focus is changing an object's state or completing a manipulation task. Hand mechanisms and joint hardware belong under Robot hardware and key components.
96 selected · 47 in the last 30 days
arXiv cs.RO ·
Paper analyzes agentic manipulation policies: AMP1 achieves 85.6% zero-shot success rate
The paper proposes agentic manipulation policies (AMP), in which a generalist AI model directly controls a robotic arm and adjusts its actions as the task progresses. The authors' reference implementation, AMP1, runs unchanged across single-arm, bimanual, and mobile manipulation.
至简动力 · 微信公众号 ·
Zhijian Dynamics and Hangcha Group deploy robot sorting line for supermarket front warehouses
On November 3, Zhijian Dynamics and Hangcha Group completed the deployment of the first robot sorting line for a supermarket front warehouse, connecting the full workflow from AMR merge feeding, robot autonomous planning and dexterous grasping and turning, and scan verification to order distribution. The line uses the iX robot body that Zhijian Dynamics customized for Hangcha, and relies on visual perception and VLA task planning to handle boxed, bagged, bottled, and other product forms without the need to model each SKU separately. Measured single-machine sorting efficiency reaches up to 450 items per hour, with accuracy stable above 98%, and under full load it can support 24-hour continuous fault-free operation.
PsiBot/灵初智能 ·
Lingchu Intelligence and collaborators propose FAFM, a continuous action generation method for heterogeneous-frequency data, accepted to NeurIPS 2026
Lingchu Intelligence, together with Beihang University, Peking University, and The Chinese University of Hong Kong, proposed a frequency-aware flow matching method called FAFM; the paper was accepted to the NeurIPS 2026 main conference. The method uses the discrete cosine transform (DCT-II) to represent actions as frequency-domain coefficients corresponding to real time, performs flow matching in coefficient space and constrains the first-order time derivative, requires no additional learnable parameters, and can be used independently or integrated into VLA models such as π₀ and π₀.₅.
PsiBot/灵初智能 ·
PKU-Spirit AI Joint Lab's RoboFFT Accepted to CoRL2026, Uses Reinforcement Learning Post-Training to Generate Robotic Policies
RoboFFT, proposed by the PKU-Spirit AI Joint Lab, has been accepted to CoRL2026. It is a reinforcement learning post-training method for generative robotic policies that reuses the forward noising process from diffusion model and flow model pretraining to construct an approximate probability ratio for PPO-style clipped updates.
arXiv cs.RO ·
TacClaw-Infinity: A Large-Scale Vision-Tactile-Language-Action Dataset for Dexterous Manipulation
The research team released TacClaw-Infinity, a large-scale structured Vision-Tactile-Language-Action (VTLA) dataset for contact-rich manipulation, spanning over 10,000 hours, 1 million episodes, and 1 billion frames across more than 1,000 task types.
arXiv cs.RO ·
From Teleoperation to Long-Horizon Dexterity: Evaluating Visuomotor Skills and Offline Proxies for Dexterous Manipulation
The research team used a five-fingered robotic hand to grasp and insert RJ45 connectors, evaluating 281 imitation-learning policies spanning seven policy families in approximately 1,700 real-robot trials. Controlled ablations showed that observation and action representations had a greater impact than conventional optimizer and sampling choices. For point-cloud policies, region-of-interest cropping, representation in the robot-base frame, and normalization within the point encoder each improved success by 70 to 100 percentage points. For the vision-language-action policy, switching to absolute action prediction improved insertion success by up to 70 percentage points.
Leiphone Robotics ·
Columbia's Yunzhu Li team presents FlexiTac open-source tactile sensor progress at IROS 2026
At IROS 2026, Columbia University's Yunzhu Li team presented progress on FlexiTac, an open-source flexible piezoresistive tactile sensor platform, a year and a half after its open-source release. The sensor can be assembled in 3 minutes, bent and cut, and wrapped around gloves, fingertips, or robot skin. The team has integrated it into LeRobot and modified the UMI handheld device to add tactile recording, enabling synchronized visual-tactile data collection and policy pretraining. ADI is advancing a commercial version with tactile resolution five times that of a human finger, manufactured at scale using semiconductor fabrication processes.
HuggingFace Daily Papers ·
RoboArchitect: Automating the Design of Robotic Agents with Persistent Memory
RoboArchitect lets a coding model observe robot rollouts, diagnose failures, and iteratively revise the agent harness around a frozen policy. Without updating any model weights, it raises average success from 9.7% to 43.3% (4.5x) on unseen scenes and from 12.7% to 40.2% (3.2x) on unseen tasks.
CMU Robotics Institute ·
CMU proposes Wiggle and Go: estimating physical properties of ropes by wiggling to plan manipulation
A team at CMU's Robotics Institute has proposed the Wiggle and Go system, in which a robot first briefly wiggles a rope or cable while an overhead camera records how the waves propagate; a computer vision algorithm then tracks the motion and estimates the object's physical properties, which are used to plan subsequent actions without repeated trial and error. The model is trained entirely in simulation, and properties are then estimated from the motion of real ropes being wiggled to improve prediction accuracy on real hardware. The research has been accepted to the 2026 Conference on Robot Learning (CoRL) and will be presented next month in Austin; it is partly funded by the U.S. National Science Foundation.
机器之心 · 微信公众号 ·
X-Era AI opensources 4D world action model E0.5, real-robot success rate surpasses π0.5
X-Era AI has open-sourced its native 4D world action model E0.5, achieving overall average success rates of 85.0% and 88.3% on the AgileX Piper dual-arm robot and the Zerith H1 humanoid robot, respectively, 13.3 and 26.7 percentage points higher than π0.5.
戴盟机器人 ·
Daimon Robotics completes hundreds of millions in strategic financing, led by Ant Group
Daimon Robotics announced the completion of a strategic funding round of hundreds of millions, led by Ant Group with existing shareholders oversubscribing, just two months after its hundred-million-yuan Series A. The company also launched its tactile-anchored world model Daimon-TWM, with parameter scale at the 10B level, capable of real-time inference on the NVIDIA RTX 5090 platform, and claims that its average success rate on contact-intensive manipulation tasks is twice that of π0.5. Daimon has also built the tactile full-modality dataset Daimon-Infinity; after the first 10,000 hours of data were open-sourced, it received nearly 5 million downloads on the ModelScope community.
HuggingFace Daily Papers ·
CaPtain: A Post-Training Pipeline for Code-as-Policy Robot Agents
CaPtain proposes an open post-training pipeline that trains small open vision-language models such as Qwen3.5-4B into code-as-policy (CaP) robot agents that do not rely on VLAs, frontier models, or privileged state at test time.
Yaskawa ·
Yaskawa Electric and GAZOO Racing to Bring AI Autonomous Welding Robot Technology to GR KART Manufacturing Site
Yaskawa Electric and Toyota GAZOO Racing have jointly developed AI-driven autonomous robot production technology, with deployment beginning in September 2026 at the Gamagori GR KART workshop. The technology builds on the SFA method (Sequence Freezing Arc Welding) jointly developed by the two parties in 2024, and uses MOTOMAN NEXT robots equipped with GPUs and AI to autonomously recognize the state of pipe frames, complete welding, confirm and correct quality, and analyze appearance images, welding sounds, and various data in an integrated manner.
arXiv cs.RO ·
FTP-1: A Generalist Foundation Tactile Policy Across Tactile Sensors
The research team proposes FTP-1, a generalist foundation tactile policy pretrained across multiple tactile sensors and embodiments. It uses heterogeneous encoders to map image-, array-, and state-based tactile signals into unified morphology-aware latent tokens, which are jointly modeled by a shared tactile Transformer expert.
机器之心 · 微信公众号 ·
Ropedia Releases Six Research Results, Exploring How First-Person Human Data Can Be Turned into Robot Capabilities
Ropedia released six studies at the first Ropedia Super Week, held October 19 to 23, centered on how first-person human video can be turned into training and execution information usable by robots.
arXiv cs.RO ·
RynnVLA-Latent: Scaling Robotic Manipulation Foundation Models with 3D-Grounded Latent Actions
The research team proposes the RynnVLA-Latent framework, which uses RynnLAM to learn continuous, 3D-grounded latent actions from visual changes without native robot control signals, converting 30.1K hours of human, robot, and simulation video into 745.52M latent action descriptors for policy pretraining.
机器之心 · 微信公众号 ·
RoboCoach: Using World Models to Locate Weak Subtasks and Improve Long-Horizon Task Success Through Targeted Teaching
Zhang Changshui and Cui Sen's team at Tsinghua University propose RoboCoach, an embodied intelligence system that uses the world model CoachWorld to run closed-loop trials of long-horizon tasks in imagination, identify the first weak subtask that times out, and request targeted human teaching for it, updating only the corresponding skill expert. Under a fixed demonstration budget, the success rate rises from 13.3% to 75.0% on Franka and from 40.0% to 83.8% on AgileX, while the uniform collection baseline reaches only 30.0% and 47.5%, respectively. On four unseen new task routes, the average success rate is 35.0%, compared with 0% for the shared-policy baseline.
中科慧灵 · 微信公众号 ·
CASBOT completes several-hundred-million-yuan A++ round to advance embodied intelligence mass production and delivery
CASBOT completed an A++ funding round of several hundred million yuan, jointly invested by Zhilai Investment, Yonghua Investment, Maotian Investment, Yuanhe Chenkun, Guoke Kezhi, Luning Investment and others. The funds will be used for product mass production and delivery, R&D iteration of embodied brain technology, and market expansion. The company's self-developed CASBOT PA perception-to-action model has been validated at actual workstations in a shoe factory in Putian, achieving a cycle time of 7 seconds per piece for the outsole stamping process and 18 seconds per pair for sole pressing. In 2026, its total orders for embodied shoe-making robots exceeded 400 million yuan, with equipment production scheduling reaching the scale of several thousand units.
HuggingFace Daily Papers ·
Rollback: Using World-Model Backtracking of Counterfactual Experience to Improve Robot Policies
Rollback proposes a policy improvement paradigm that turns an action-conditioned world model from a one-way simulator into a backtrackable counterfactual engine: it returns to key decision points, branches to try different actions, and compares the outcomes, thereby distilling counterfactual results into action-level supervision without learning a separate value model.
机器之心 · 微信公众号 ·
Tsinghua team builds HandsOn dexterous manipulation benchmark with 66 tasks to evaluate robot bimanual capabilities
Ding Ning's team at Tsinghua University, together with researchers from Beijing University of Posts and Telecommunications, Peking University, and Nature Will, built HandsOn, a simulation platform and evaluation benchmark for cross-embodiment dexterous manipulation, containing 66 manually verified tasks and 18,000 human simulation teleoperation demonstrations.