AI & Perception

A guide to ω-0's 3-stage architecture and training pipeline — the latent predictive WAM that achieves 81.8% success rate on 11 household tasks, enabling humanoids to walk and grasp simultaneously.

OpenHLM (arXiv 2606.22174): 3-phase empirical recipe — 32-DOF joint-based teleoperation, π0.5 VLA, HuMI co-training — outperforms GR00T N1.6 and Ψ₀ on Unitree G1 using under half the demo time.

Load G1 MCAP bag recordings with the DataLoadMCAP plugin, drag all 23 joint channels into a synchronized multi-panel grid, save your layout as XML, and create phase portraits with XY Scatter.

Understand C-space, RRT/RRT-Connect/PRM via OMPL, use MoveGroupInterface C++ and moveit_py Python to plan collision-free paths and execute them in RViz with MoveIt2.

A step-by-step guide to Ark v1.5 — Python-first robot learning framework with a Gym-style API, native ROS, ACT and Diffusion Policy out of the box.

Step-by-step guide to install and run Xiaomi-Robotics-0 — a 4.7B VLA combining Qwen3-VL and Diffusion Transformer with 80ms real-time inference on RTX 4090.

Explore Dense Object Nets, DenseFusion, and DenseMatcher — three dense visual descriptor technologies revolutionizing how robots see and grasp objects.

Deep dive into Google's Gemma 4 — open-source multimodal AI with agentic capabilities, running on Jetson and Raspberry Pi for robotics.

Analyzing Google's Gemma 4 architecture — from on-device AI to practical applications in robot control, perception and agentic workflows.

Step-by-step guide to building the Berkeley Humanoid Lite — an open-source 3D-printed humanoid with 24 DOF and RL-based sim-to-real locomotion from UC Berkeley.

FlashSAC — a new off-policy RL algorithm that outperforms PPO in both speed and performance across 100+ robotics tasks.

Techniques for transferring models from simulation to real robots — domain randomization, system identification, and best practices.

Practical tutorial — fine-tune OpenVLA on custom data, LoRA, quantization, and deploy on a real robot.

Why 3D spatial awareness matters for VLA — Ego3D Position Encoding and Adaptive Action Grids.

Explore tactile sensing technology — from resistive, capacitive to vision-based tactile, and applications in soft object grasping.

History and evolution of Vision-Language-Action models — what each model solves and the trade-offs.

Comprehensive overview of foundation models for robotics — how RT-2, Octo, and OpenVLA are transforming how robots learn manipulation and navigation.

Why diffusion models are breakthrough for robotics — multimodal distributions, high-dimensional actions, and stability.

Analyzing ACT — why predicting multiple actions together is better, CVAE encoders, and temporal ensembling.

Why imitation learning is more important than RL for many manipulation problems — how to collect data and train policies.

Overview of RL algorithms for robotics — PPO, SAC, TD3 and guide to choose the right algorithm for each robot problem.

Step-by-step guide deploying YOLOv8 with TensorRT on NVIDIA Jetson Orin Nano — from model export to real-time 60 FPS inference.

How to use RL to teach robots walking on two legs — from reward design, sim-to-real transfer to deployment on actual hardware.

Summary and analysis of the most influential robotics papers — from foundation models for robots, dexterous manipulation to sim-to-real transfer.

Guide to deploying Edge AI with NVIDIA Jetson and TensorRT — optimize real-time inference for robots and embedded applications.

Overview of AI trends in Robotics 2025 — foundation models, sim-to-real transfer, and Embodied AI transforming the industry.

Guide to applying Computer Vision for automated quality inspection with YOLOv8 and industrial cameras on production lines.