2026-11-09 カリフォルニア大学バークレー校（UCB）
Goldberg and his team released an industry-standard benchmark for evaluating the performance of robots across industrial tasks, examples of which of shown here.
＜関連情報＞
- https://news.berkeley.edu/2026/11/09/recent-advances-in-ai-are-creating-a-paradigm-shift-for-robotics/
- https://arxiv.org/abs/2607.05369
GaP：変分自動化タスクのためのグラフ・アズ・ポリシー型マルチエージェント自己学習ハーネス GaP: A Graph-as-Policy Multi-Agent Self-Learning Harness For Variational Automation Tasks
Kaiyuan Chen, Shuangyu Xie, Letian Fu, Justin Yu, William Pacini, Sandeep Bajamahal, Hudson Kim, Jaimyn Drake, Daehwa Kim, Haoru Xue, Jonathan Francis, Christian Juette, Peter Schaldenbrand, Muhammet Yunus Seker, Ruwan Wickramarachchi, Uksang Yoo, Guanzhi Wang, Adithyavairavan Murali, Balakumar Sundaralingam, S. Shankar Sastry, Yuke Zhu, Linxi “Jim” Fan, Spencer Huang, Ken Goldberg
arXiv last revised 4 Nov 2026 (this version, v3)
DOI:https://doi.org/10.48550/arXiv.2607.05369
Abstract
For robots to work reliably in commercial and industrial applications, recent advances in agentic coding systems have potential to combine interpretable robot programming with the open-world adaptability of model-free policies. We focus on “Variational Automation” (VA), a class of tasks that have larger variations in object geometry and pose than fixed automation. Model-free policies often struggle to close the reliability gap for VA tasks, which must be executed persistently and reliably in commercial and industrial applications. Motivated by prior work on Task and Motion Planning (TAMP) and the Robot Operating System (ROS), we introduce Graph-as-Policy (GaP), a multi-agent coding harness that generates directed computation graphs with perception, planning, and control nodes from a Modular Open Robot Skill Library (MORSL). GaP generates an internal simulation environment to rehearse task instances with different graphs in parallel to iteratively refine the graph structure and parameters to improve success rates and throughput. Evaluation with 8 new open VA task benchmarks, 4 in simulation and 4 in real-world, suggests that GaP can achieve success rates that significantly outperform baselines. Details, code, and data: this https URL
