logo Mr.Robota 具身智能学习手册 中文
Chapter 15: ATEC2026 Lightweight Code

ATEC2026 Online Competition: Post-Competition Review, Public Solutions, and Reproduction Entry

This directory serves as the unified entry for ATEC2026 in Chapter 15 of Every Embodied, containing task definitions, L0 task practices, Task B garbage collection review, Task D public solution analysis, Task E desktop organization reproduction, lightweight code, and public resource descriptions.

This is not a championship solution, and it does not guarantee any online scores. The tutorial breaks down a real embodied AI competition into readable, verifiable, and reproducible engineering materials, and clearly distinguishes between official evidence, local debugging evidence, and results reported by external competitors.

Directory Structure

text15-Challenge竞赛/ATEC2026/
├── README.md
├── L0-机器人徒步/                 # Task A / B2Piper locomotion 复现与评估
├── L0-桌面整理TaskE/              # Task E / Piper 桌面抓取与 ACT 复盘
├── TaskB-B2Piper/                 # Task B / B2-Piper 垃圾收集专题
├── docs/                          # Task A/B/D/E 共性边界与发布文档
├── code/                          # 轻量 adapter、参考仓库审计和检查脚本
└── references/                    # 外部公开方案、固定 commit 与许可证索引

Task Overview

Task Robot/Ability Entry Point of This Directory Public Conclusion Boundaries
Task A / L0 B2Piper Off-road Hiking L0-机器人徒步/ Focus is on the official baseline, local evaluation, trajectory tracking, and checkpoint selection
Task B B2-Piper Garbage Collection TaskB-B2Piper/ Public complete debugging and observation boundaries; no fully verified final policy
Task D Box Pushing Over Obstacles docs/03_公开方案与Logic-TARS.md Focus on the public Logic-TARS state machine, LiDAR, and action adaptation
Task E / L0 Piper Desk Organization L0-桌面整理TaskE/ The best online result for ACT seed1 best is [15.00], not a perfect solution
  1. Task definition and observation boundaries
  2. Problem list and solutions
  3. Public solution and Logic-TARS interpretation
  4. Reproduction, HF, and GitHub release
  5. Archiving reconciliation and local cleanup
  6. Task B special archive

Public Resources

Reproduction Agreement

  • GitHub only stores tutorials, lightweight code, experimental boundaries, fixed external commits, and masked Workspace Memory.
  • Large datasets, model weights, official source code snapshots, videos, and logs are recorded on Hugging Face according to licenses and SHA-256.
  • Complete simulation still requires matching Isaac Sim/Isaac Lab, GPU, Python dependencies, official runner, and evaluator; GitHub tutorials cannot be used as a one-click environment.
  • Environment cameras, truth values, oracle prefix, script grippers, and phase state machines can be used for diagnosis, but protocol boundaries must be indicated; they cannot be used as formal policy inputs or complete success evidence.
  • Raw training caches, private logs, tokens, server credentials, and unauthorized SDKs do not enter the public repository.