Content types
Guides and practice
Reusable methods, tool usage, explanations, and engineering retrospectives for robotics development, integration, debugging, training, and operations. A tool launch belongs under Product updates; content centered on a judgment or argument belongs under Opinions.
5 selected · 2 in the last 30 days
Reddit r/robotics ·
PrismaX shares π0.5 policy transfer across YAM devices: fine-tuning ablations, latency bug, and 16GB VRAM deployment
The PrismaX team shared its practice of transferring a π0.5 policy trained on one YAM device to another YAM device, covering three parts: fine-tuning ablations, latency troubleshooting, and VRAM compression. On fine-tuning, training only the action expert yielded a 51% grasp rate and a 12% drop rate; full fine-tuning gave 89% and 53%; r=128 LoRA gave 84% and 59% while using 32GB. Strong lighting roughly halved the performance of the checkpoint trained only on the action expert.
Xbotics具身智能实验室 · 微信公众号 ·
How to Choose a Robot Simulator: Same Success, Tenfold Contact Force Gap
The article interprets a simulator comparison report released by Manda Robotics in early October, running about ten sets of experiments with the same Franka 7-axis robotic arm and the same control program on four physics engines: PhysX, MuJoCo, MuJoCo Warp, and Genesis.
Agile Robots/思灵机器人 ·
Agile Robots and Idealworks detail edge AI inference stack, running VLMs on Jetson AGX Xavier with custom TensorRT plugins
Agile Robots and its subsidiary Idealworks describe their edge AI deployment stack since 2018, covering five layers: hardware, BSP, inference pipeline, inference framework, and quantization.
RoboParty · 微信公众号 ·
RoboParty Lab Established, Open-Sources Three Humanoid Robot Toolchains for Training, Control, and Data
RoboParty announced the establishment of RoboParty Lab and open-sourced three humanoid robot toolchains: the supervised learning training framework MimicLite, the unsupervised reinforcement learning control framework UFO, and the motion retargeting tool hhtools.
Toyota Research Institute Robotics ·
Toyota Research Institute explains statistical thinking for robot policy evaluation: from rigorous A/B testing to effective visualization
The Toyota Research Institute (TRI) published a tutorial article introducing a statistical A/B testing method based on success/failure labels for robot policy evaluation.