Whole-body VLA

Horizon Robotics' HoloMotion-1 uses a 400M-param Sparse MoE Transformer to achieve zero-shot whole-body humanoid control on Unitree G1 — trained on in-the-wild video, no real-robot data needed.

MIT Han Lab's VLASH makes VLAs real-time via future-state-aware asynchronous inference — 11.8× lower reaction latency, no architecture changes, open-source.

Complete guide to training SONIC whole-body controller with GR00T-WholeBodyControl open-source on 100M+ motion capture frames, deployed on Unitree G1.

CoorDex uses body and hand latent priors to train Unitree G1 for continuous walk-grasp-carry without stopping. Open-source code from UNC Chapel Hill.

A practical guide to SLIM-0.5B, a compact VLA manipulation policy with action-grounded predictive latents on LIBERO.

Deep dive into DyPES-VLA — cross-embodiment SOTA: 98% LIBERO, 89% RoboTwin 2.0, 75.6% real-world across 3 robots using shared Dynamics Prior and MoE Action Head.

A practical guide to πR² for GR00T-N1.7: architecture, setup, fine-tuning, 25 Hz inference, and manipulation results.

Run MiniVLA on LIBERO/MuJoCo, add perturbation tests, and understand how to report a 97.92% robustness success rate.

A practical World-to-Wrist VLA guide: wrist-view generation, wrist CoT labels, LeRobot data setup, training, inference, and results.

A practical T-Rex guide: tactile-reactive VLA architecture, LeRobot v3.0 dataset path, training, inference, and benchmark results.

TurboVLA achieves 97.7% on LIBERO with 0.2B parameters, 31.2 ms latency, and 0.9 GB VRAM on RTX 4090 — no LLM needed. Full guide: install, train, evaluate, and deploy.

A practical guide to LoRA fine-tuning DM0.5 for SO101 Pick Cube, from OpenDM setup to training, inference, and RoboTwin2.0 evaluation.

A technical guide to RL²-VLA: steering VLA manipulation policies via offline RL in latent space at test time, gaining +26% real-robot success without retraining the base model.

FM-VLA compresses force/torque history into compact tokens via VAE, enabling VLAs to count contact events and track interaction progress — 83.3% success on AgiBot G1.

A practical guide to Pelican-VLA 0.5, Bottleneck Tokens, LeRobot 3.0 data, training recipe, inference, and RoboTwin results.

ResVLA (ICML 2026): using Residual Diffusion Bridge to anchor VLA policies from intent, reducing noise and improving robustness for robot manipulation.

A beginner guide to AXIS: collect manipulation data with browser teleoperation, clean it, and fine-tune π0.5 with OpenPI.

A hands-on guide to VLA-Corrector: adaptive action horizons, LVM, OGG, LeRobot setup, training, inference, and results.

Deploy guide for Robo-ValueRL — X-Humanoid's open-source framework that integrates value estimation into VLA-RL to achieve millimeter-precision on real-world manipulation tasks.

How to use Robometer, TOPReward reward models, lerobot-eval CLI with 6 new benchmarks, and DAgger to close the automated RL loop for manipulation VLA in LeRobot v0.6.

A practical guide to installing, fine-tuning, and deploying InternVLA-A1.5 on LeRobot datasets with latent foresight for manipulation VLA.

Complete guide to fine-tuning and deploying GalaxeaVLA G0.5 — a unified autoregressive VLA on Qwen3.5 2B achieving 98.9% on LIBERO and 82.5% zero-shot DROID, open-source from HuggingFace to real robots.

A practical guide to using Cyclo Intelligence Behavior Trees to orchestrate GR00T N1.7 whole-body VLA on humanoids.

Open-source VLA from USC PSI Lab that beats GR00T N1.6 with only 80 demos. Full pipeline: install, teleoperation, 3-stage training, and deploy on Unitree G1.

Install, post-train, and evaluate LingBot-VLA 2.0, a 55D cross-embodiment VLA for RoboTwin 2.0.

A hands-on guide to OpenHLM: native whole-body VLA for Unitree G1 with HuMI co-training, LeRobot data, training, and inference.

End-to-end pipeline: Isaac Teleop → LeRobot v0.6 → GR00T N1.7 — collect teleop data, fine-tune the VLA, and deploy your manipulation policy on a real robot arm. Updated July 2026.

Technical deep-dive into LingBot-VLA 2.0 — a 6B-parameter open-source VLA with 60,000 hours of training data, MoE Action Expert, Dual-Query Distillation, and cross-embodiment mobile manipulation outperforming π0.5.

A hands-on guide to DexVerse, the open-source benchmark for testing OpenVLA, π0.5, and diffusion policies on dexterous manipulation.

Complete guide to setting up OpenWBC — an open-source VR teleoperation system using Apple Vision Pro + OpenHomie to control Unitree G1 and collect whole-body VLA training data for GR00T N1.5.

MoT architecture unifying video prediction and robot policy in a shared causal latent space — 98.5% on LIBERO, outperforms π0.5 across all 6 real-world manipulation tasks.

FORCE tackles two core failures in VLA RL fine-tuning — unstable Q-function and low-quality exploration — through Value-Calibrated Warm-Up and Self-Distillation, achieving a 79% absolute success rate improvement without any human intervention.

TGRPO combines LLM-generated dense rewards with dual-level advantage estimation (step + trajectory) to fine-tune OpenVLA-7B on LIBERO, reaching 91% success rate — beating SFT by 4.6%.

InternVLA-A1 unifies semantic understanding, visual foresight, and action execution in one Mixture-of-Transformers architecture — outperforming π0.5 by +26.7% on dynamic manipulation tasks.

Deep dive into Qwen-VLA — Alibaba's unified VLA using Qwen3.5-4B + DiT decoder, one set of weights for manipulation, navigation, and heterogeneous robots.

XPENG Robotics introduces ROVE — a post-training RL framework that leverages imperfect human interventions to improve dexterous humanoid manipulation policies.

Stanford's InSight framework enables VLA models to autonomously acquire new manipulation skills by decomposing primitives, identifying skill gaps, and running a VLM-guided data flywheel — no human demonstrations required.

UC Berkeley's LeVERB is the first hierarchical framework bridging VLA and humanoid whole-body control via a learned latent verb space — achieving 58.5% success with zero-shot sim-to-real on Unitree G1.

UC Berkeley's LeVERB is the first framework and benchmark bridging VLA with humanoid Whole-Body Control via a latent action space. 58.5% success rate, zero-shot sim-to-real on Unitree G1.

VLA-JEPA combines Qwen3-VL with V-JEPA2 latent world model, runs at 10Hz on RTX 3080, fine-tuned with only 13 demos. Full guide for installation and training on LeRobot.

ROVE (XPENG Robotics) applies Optimistic Value Estimation to turn imperfect humanoid teleoperation data into RL signal for iterative VLA post-training.

A hands-on guide to RLinf-Co — open-source framework combining RL and real data to train π₀/π₀.₅ VLAs far beyond pure imitation learning.

A practical guide to DREAM-Chunk, reactive action chunking with a latent world model for robust VLA robot execution.

A practical guide to MemoryVLA++: PCMB memory, latent imagination with a world model, training, inference, and long-horizon results.

A practical guide to installing, running, fine-tuning, and evaluating Hy-Embodied-0.5-VLA for bimanual robot manipulation.

A practical guide to WEAVER, a multi-view world model for evaluating, improving, and steering π0.5 VLA manipulation.

A beginner-friendly guide to M3imic: idea, architecture, Isaac Lab setup, training, inference, and Unitree G1 results.

Step-by-step walkthrough of the RISE training pipeline: environment setup, LeRobot data preparation, offline policy training, dynamics model, and online self-improvement loop on 4–8 GPUs.

RISE uses a compositional world model so VLA policies can improve through imagined rollouts before real robot deployment.

A repo-level guide to GR00T-WholeBodyControl through decoupled_wbc, gear_sonic, and gear_sonic_deploy.

A beginner-friendly walkthrough for SONIC MuJoCo sim2sim and Isaac Lab eval, from sample_data paths to success_rate and MPJPE targets.

Convert BONES-SEED CSV/BVH to motion_lib PKLs, filter motions, and configure SONIC training paths.

A practical walkthrough of SONIC C++ deployment with ONNX, TensorRT, ZMQ, observation config, and visualization.

A practical guide to SONIC PICO teleop, zmq_manager, data export, and LeRobot v2.1 datasets for VLA training.

A practical guide to ETH's course from MDPs, imitation learning and RL to VLA/foundation models for robotics.

DIRECT learns when a robot planner should use cheap or expensive VLM compute, preserving success while reducing latency.

A practical guide to LIBERO-Occ and Viewpoint Imagination for evaluating, training, and running VLA policies under occlusion.

Run LabVLA — the first VLA model for scientific lab robots, combining Qwen3-VL-4B with DiT flow-matching and LeRobot v2 format. 71.1% on LabUtopia benchmark.

A practical guide to LeCAR-Lab ASAP: motion tracking, delta action training, policy fine-tuning, and Unitree G1 sim-to-real deployment.

A practical World Pilot guide for using World-Action Priors to improve zero-shot OOD robustness in VLA robots.

A practical guide to UniIntervene: value-risk triggering and memory-guided recovery for real-world robot RL fine-tuning.

A practical guide to TREAD: segment robot trajectories, relabel subtasks with VLMs, and fine-tune stronger VLAs on LIBERO.

A practical guide to using SARM in LeRobot to learn task progress from video, score rollouts, and improve VLA policies with RA-BC.

A practical OASIS guide: build assets, teleoperate in Isaac Lab, render randomized trajectories, train whole-body policies, and deploy zero-shot.

Set up OpenWBT for Unitree G1, verify the ONNX policies, run MuJoCo teleop, then move carefully to real hardware.

Run TWIST2 from ONNX checkpoint to real G1: Redis bus, PICO teleop, sim2sim, sim2real, GUI and data recording.

Build the EgoHumanoid path from human/robot data to view alignment, action alignment, LeRobot, training and G1 deployment.

Build VIRAL with Isaac Sim 5.1: PPO teacher, RGB DAgger student, Hydra fields, ONNX export, and EgoHumanoid comparison.

Run FRoM-W1 from text prompts to H-GPT motion, H-ACT retargeting, and G1 tracking policy, then compare it with VIRAL.

Deploy CLONE on G1 with Apple Vision Pro, LiDAR odometry, an MoE policy, and a practical stack-selection table.

Install, evaluate on LIBERO, and fine-tune Embodied-R1.5-VLA for robot manipulation using open-source checkpoints.

A beginner guide to building YUBI, collecting bimanual LeRobot data, and training/deploying VLA policies.

Turn WholeBodyVLA's evaluation table into practical subgoal scorecards, ablations, and failure logs for humanoid testing.

A beginner map of the WholeBodyVLA stack: VLM, two LAMs, 10 Hz decoder, and 50 Hz LMO control.

A practical guide to running Omega-QVLA for compressing GR00T N1.5 and pi0.5 to W4A4 for edge VLA manipulation.

Design the first humanoid VLA data session with two operators: camera, state, action, language, episode rules, and throughput.

Compare keyboard, SpaceMouse, OpenXR hand tracking, and GR00T WBC by latency, safety, and the action type you need.

Design humanoid VLA raw logs with MCAP: record, writer YAML, replay, Foxglove inspection, and LeRobot/Robo-DM export.

Design a two-tier data lake: LeRobot Parquet+MP4 for sharing and Robo-DM .vla trajectories for high-throughput VLA training.

An Isaac Lab Mimic workflow for filtering demos, expanding 5 demos into 1000 trials, and QA before BC training.

How to evaluate WholeBodyVLA, 50 Hz LMO, and WBC ONNX controllers while scaling humanoid data collection to 20 operators.

A complete guide to HEX — the first whole-body VLA for full-sized humanoid robots, supporting 7 embodiments, open-source, built on Qwen3-VL + MoE UPP + DiT flow-matching.

A practical ProcVLM guide: turn robot videos into dense progress rewards for RL fine-tuning VLA manipulation policies.

A beginner guide to ACoT-VLA: action chain-of-thought, EAR/IAR architecture, LeRobot-format data, training, inference, and results.

A beginner-friendly guide to StressDream: stress-test robot manipulation policies with video world models before deployment.

Train VIRAL and DoorMan for Unitree G1 in Isaac Lab: setup, teacher-student training, DAgger, GRPO, inference, and sim-to-real.

A practical guide to fine-tuning GalaxeaVLA G0Tiny 250M with LeRobot datasets for real robot manipulation.

A beginner-friendly deep dive into OpenVLA 7B: idea, architecture, setup, fine-tuning, inference, and real robot results.

A beginner-friendly deep dive into GR00T N1.7, SONIC, data collection, fine-tuning, inference, and humanoid whole-body VLA.

Part 1 of the GR00T whole-body VLA data pipeline: download public datasets, validate GR00T-LeRobot format, fine-tune, and run inference.

Part 3 of the GR00T whole-body VLA data pipeline: when real data is needed, VR teleop with SONIC, LeRobot export, real/sim/public mixing, and deployment.

Part 2 of the GR00T whole-body VLA data pipeline: generate Isaac Lab/IsaacLab-Arena data, convert to GR00T-LeRobot, and train sim-only or mixed datasets.

Part 4 of the GR00T whole-body pipeline: process Bones-SEED/SOMA motion data, train or fine-tune SONIC, evaluate checkpoints, and export ONNX for C++ deployment.

A beginner guide to GR00T whole-body VLA synthetic data, LeRobot format, modality.json, fine-tuning, inference, and results.

Wall-OSS-0.5 is an open-source 4B VLA for zero-shot real-robot manipulation, integrated with LeRobot and gradient-bridged co-training.

A practical GRAIL guide for creating synthetic data from 3D assets and video priors to fine-tune whole-body VLA policies on Unitree G1.

A practical software stack for humanoid robots: realtime control, ROS 2, simulators, teleop data, LeRobot, VLA policies, deployment, and monitoring.

A practical deep dive into WholeBodyVLA, LMO RL, and the newest WBC + VLA stack for humanoid loco-manipulation.

A practical deep dive into VLA-RFT: world-model rollouts, verified rewards, GRPO fine-tuning, GitHub code, LIBERO training and results.

A practical guide to Wall-OSS-0.5, the open-source 4B zero-shot VLA for robot manipulation, from paper details to LeRobot training.

How to monitor, calibrate, and constrain VLA actions before deploying SmolVLA or OpenVLA on LeRobot robots.

Step-by-step guide to OpenHelix — install, train and deploy a Dual-System VLA achieving SOTA on CALVIN ABC-D with LLaVA-7B + 3D Diffuser Actor, beginner-friendly.

Full guide to A1 VLA open-source: 72% lower latency on Franka/AgiBot via Inter-Layer Truncated Flow Matching, achieving SOTA on LIBERO 96.6% and VLABench 53.5%.

Build the HuggingFace LeRobot Humanoid — a $2,500 fully open-source 3D-printed bipedal robot. BOM, MJLab sim, RL training, sim2real deploy.

Deploy GalaxeaVLA G0 Plus — a zero-shot Pick Up Anything VLA via Docker in 30 minutes. Open-source code + checkpoints on HuggingFace.

X-VLA tutorial — flow-matching 0.9B VLA hitting SOTA on 6 sims + 3 real robots, native LeRobot, open-source on HuggingFace.

Guide to ABot-M0 from AMAP CVLab Alibaba: VLA trained on 6M+ trajectories, predicts clean actions instead of noise, full code + weights open-source.

Step-by-step guide to OpenHelix VLA-Adapter — train a tiny-scale 0.5B VLA in 8 hours on a single consumer GPU, hit SOTA on LIBERO, deploy on Franka/UR-5.

ICLR 2026 — hands-on pipeline from teleop collection through unified latent VLA training to whole-body loco-manipulation deployment on AgiBot X2.

NVIDIA NVlabs proves action as text reaches 94.7% on LIBERO, beating pi_0 and GR00T-N1 with zero architecture modification — just Qwen2.5-VL-3B.

Detailed guide to RDT2 from THU-ML — a foundation model that zero-shot deploys to bimanual UR5e and Franka, with open-source code.

Step-by-step guide to the complete WholebodyVLA training pipeline — egocentric data collection, LAM training, VLA fine-tuning, LMO RL policy, and inference deployment.

A technical deep-dive into OpenHelix — the open-source dual-system VLA that pairs LLaVA-7B (System 2) with a 3D diffusion policy (System 1) via a learned ACT token, achieving SOTA on CALVIN.

Deploy Pi0-FAST on Unitree G1 with whole-body loco-manipulation in LeRobot v0.5.0 — from setup, teleoperation, to real-time inference with RTC.

Complete guide to fine-tuning NVIDIA GR00T N1.7 with EgoScale's 20,854-hour egocentric video dataset — from setup to deploying your policy on a humanoid robot.

Step-by-step guide to fine-tune NVIDIA GR00T N1.6 — the 3B VLA model combining Cosmos Reason 2 for controlling humanoid robots from images and language.

Deep dive into NVIDIA GEAR-SONIC — training a whole-body controller for humanoid robots with BONES-SEED dataset and VR teleoperation.

Deep-dive into the WholebodyVLA codebase — latent action architecture, LMO RL policy, and building a whole-body loco-manipulation pipeline for humanoids.

Step-by-step guide to building Vision-Language-Action models with StarVLA — a Lego-like modular framework from ICLR 2026 supporting 4 action head architectures.

Step-by-step guide to fine-tune the GR00T N1 VLA model for humanoid robots using Isaac Lab and AGIBOT World data — from setup to inference.

Hands-on guide to training VLA with World Models and Reinforcement Learning using the RAMP framework from GigaBrain — open-source, 3.5B params.

Fine-tune large VLAs with LoRA on consumer GPUs, deploy to real robots with Real-Time Chunking — a production-ready workflow.

A detailed analysis of training the 7-DoF OpenArm robot for carton box grasping — comparing 3 paths: LeRobot native, SimpleVLA-RL style, and hybrid.

Step-by-step guide to setting up OpenArm, calibrating, teleoperating, and collecting 50 box-grasping episodes with LeRobot.

Train SmolVLA, ACT, Pi0-FAST for OpenArm box grasping — from fine-tuning to real robot deployment and improvement with HIL-SERL.

Set up OpenArm in Isaac Lab, collect demonstration data in simulation, and convert to SimpleVLA-RL training format.

Step-by-step guide to SFT fine-tuning and RL training with SimpleVLA-RL for OpenArm — from environment config to running GRPO.

Deploy a SimpleVLA-RL model from simulation to real OpenArm — camera setup, action mapping, and tips for reducing the sim-to-real gap.

Analyzing SimpleVLA-RL results: ablation studies, the pushcut phenomenon, real-world transfer, and 5 key lessons learned.

In-depth comparison of SimpleVLA-RL and LeRobot: RL approach, VLA models, sim vs real, data efficiency — two complementary frameworks.

Analyzing ablation studies, comparing baselines, and the 5 most important lessons from Psi0 for newcomers.

Guide to training Pi0-FAST in LeRobot — from training the FAST tokenizer, fine-tuning the model, to inference with KV-caching.

A detailed guide to using HIL-SERL in LeRobot — reinforcement learning directly on real robots with human interventions.

SimpleVLA-RL uses reinforcement learning with simple 0/1 rewards to boost VLA from 17 to 92 points — no complex reward engineering needed.

Detailed guide to fine-tuning SmolVLA — a 450M VLA model that runs on consumer GPUs, from data collection to real robot deployment.

MMaDA-VLA unifies language, vision and robot actions into a single token space via discrete diffusion — a new paradigm for VLA models.

Guide to deploying the Psi0 model, running inference in the SIMPLE simulator, and evaluating results with Real-Time Chunking.

Complete pipeline from simulation to real robot — domain randomization, camera calibration, inference optimization, and ROS 2 deployment.

Complete overview of LeRobot v0.5 — Pi0-FAST, SmolVLA, Real-Time Chunking, HIL-SERL, Unitree G1, PEFT/LoRA, and 10x training speed.

Analysis and implementation guide for UnifoLM-VLA-0 — the first open-source VLA model running directly on the G1 humanoid

ICLR 2026 — learning manipulation from egocentric video, combining VLA + RL for locomotion-aware control

Step-by-step guide to setting up the Psi0 environment and running the 3-stage training pipeline: pre-train, post-train, fine-tune.

Step-by-step guide to setting up the environment, running SFT cold-start, and RL training for SimpleVLA-RL on LIBERO and RoboTwin.

Online RL framework for VLA — surpasses pi0-FAST on 40 tasks, discovers first inference scaling law for robotics

Humanoid robots as the ultimate manipulation platform — high-DOF control, egocentric vision, and humanoid foundation models.

Explore Psi0's data recipe — why 860h of data beats 10,000h, how to process EgoDex, Humanoid Everyday, and LeRobot format.

Deep-dive into OpenVLA-OFT backbone, GRPO optimizer, dynamic sampling, and the exploration mechanisms that let VLA models self-improve.

Combining navigation and manipulation on mobile robots — extended action space, whole-body coordination, and sim environments.

Deep-dive into the Ψ₀ architecture: System-2 (VLM), System-1 (MM-DiT), System-0 (RL Controller) — the brain, hands, and legs of the robot.

Training bimanual policies for practical tasks — towel folding, water pouring, assembly. ACT vs Diffusion Policy comparison for dual-arm.

Introducing SimpleVLA-RL — using simple binary 0/1 rewards with RL to improve VLA models by 430%, no reward engineering needed.

Introducing Ψ₀ — the first open-source foundation model that teaches humanoid robots to walk and manipulate objects simultaneously.

Guide to setting up a dual-arm robot system with LeRobot — calibration, coordinate frames, and preparation for bimanual tasks.

Building policies for long-horizon tasks — hierarchical planning, curriculum learning, and failure recovery for complex action sequences.

Overview of Hugging Face LeRobot — models, datasets, hardware support, and how to get started with $100.

Expanding from single-object to multi-object manipulation — sorting, stacking, rearranging with language-conditioned policies.

Guide to training ACT and Diffusion Policy with LeRobot, comparing performance, hyperparameter tuning, and visualizing results.

Step-by-step guide to collecting demonstration data via teleoperation in simulation with LeRobot — from setup to complete dataset.

Explore LeRobot architecture from HuggingFace — dataset format, policy zoo, training pipeline, and comparison with other frameworks.