AI Agent

VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning

VADv2：通过概率规划实现端到端向量自主驾驶

Bo Jiang, Shaoyu Chen, Hao Gao, Bencheng Liao, Qian Zhang, Wenyu Liu, Xinggang Wang

机构 * Huazhong University of Science and Technology（华中科技大学） ； Horizon Robotics 纠错

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文提出VADv2，一种基于概率规划的端到端自主驾驶模型，通过概率场函数建模动作空间到概率分布的映射，利用大规模驾驶演示提升闭合回路性能，优于现有方法。

Comments Accepted to ICLR 2026. Code is available at https://github.com/hustvl/VAD

COVER:COverage-VErified Roadmaps for Fixed-time Motion Planning in Continuous Semi-Static Environments

覆盖验证的固定时间运动规划路标：连续半静态环境中的路标规划

Niranjan Kumar Ilampooranan, Constantinos Chamzas

机构 * Department of Robotics Engineering, Worcester Polytechnic Institute (WPI)（机器人工程系，沃斯特理工学院（WPI）） 纠错

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文提出COVER框架，通过增量构建覆盖验证的路标，为半静态环境提供固定时间内的运动规划解决方案，展示了更广的问题空间覆盖和更高的查询成功率。

Contact-Aware Planning and Control of Continuum Robots in Highly Constrained Environments

具备接触意识的连续机器人在高度受限环境中的规划与控制

Aedan Mangan, Kehan Long, Ki Myung Brian Lee, Miheer Potdar, Nikolay Atanasov, Tania K. Morimoto

机构 * Department of Mechanical and Aerospace Engineering, University of California San Diego（加州大学圣地亚哥分校机械与航空航天工程系） ； SceniX Inc（SceniX公司） ； Department of Electrical and Computer Engineering, University of California San Diego（加州大学圣地亚哥分校电气与计算机工程系） ； Department of Surgery, University of California San Diego（加州大学圣地亚哥分校外科系） 纠错

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文提出一种具备接触意识的规划方法，通过评估接触质量并惩罚危险交互，生成可行轨迹和接触意识雅可比矩阵，实验证明其在高度受限环境中可靠导航的能力。

Comments 15 pages, 3 figures

Trajectory Planning for Safe Dual Control with Active Exploration

安全双控轨迹规划与主动探索

Kaleb Ben Naveed, Manveer Singh, Devansh R. Agrawal, Dimitra Panagou

机构 * Department of Robotics, University of Michigan（密歇根大学机器人学系） ； Department of Aerospace Engineering, University of Michigan（密歇根大学航空航天工程系） 纠错

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文研究了一种受预算约束的双控问题，通过整合鲁棒规划与主动探索，在保证安全性和预算可行性的同时，平衡即时任务性能与长期不确定性降低。

DriveLaW:Unifying Planning and Video Generation in a Latent Driving World

DriveLaW：在潜在驾驶世界中统一规划与视频生成

Tianze Xia, Yongkang Li, Lijun Zhou, Jingfeng Yao, Kaixin Xiong, Haiyang Sun, Bing Wang, Kun Ma, Guang Chen, Hangjun Ye, Wenyu Liu, Xinggang Wang

机构 * Huazhong University of Science and Technology（华中科技大学） ； Xiaomi EV（小米电动车） 纠错

专题命中 规划决策 ：planning(title,abstract)

AI总结 DriveLaW通过统一视频生成与运动规划，提升自动驾驶中的预测与规划性能，实现视频生成与轨迹规划的一致性，取得新的state-of-the-art结果。

Comments 18 pages, 6 figures, CVPR 2026

Sampling-Based Multi-Modal Multi-Robot Multi-Goal Path Planning

基于采样的多模态多机器人多目标路径规划

Valentin N. Hartmann, Tirza Heinle, Yijiang Huang, Stelian Coros

机构 * Computational Robotics Lab ETH Zürich（机器人计算实验室ETH Zurich） 纠错

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文提出基于采样的多机器人多目标路径规划方法，解决多机器人协同任务中的路径规划问题，实现概率完备和渐进最优的规划算法。

Comments 25 pages, 17 figures

Trajectory Planning for a Multi-UAV Rigid-Payload Cascaded Transportation System Based on Enhanced Tube-RRT*

基于增强型管状RRT*的多无人机刚性载荷级联运输系统轨迹规划

Jianqiao Yu, Jia Li, Tianhua Gao

机构 * School of Aerospace Science and Technology, Beijing Institute of Technology（航天科学与技术学院，北京理工大学） ； Graduate School of Systems and Information Engineering, University of Tsukuba（系统与信息工程研究生院，筑波大学） 纠错

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文提出一种两级轨迹规划框架，通过增强型管状RRT*算法解决密集障碍环境下的规划问题，结合主动混合采样和自适应扩展策略，生成安全可行的虚拟管，并通过轨迹平滑成本减少过度转弯，提升路径效率。

Comments 15 pages, 7 figures. Under review at IEEE Transactions on Aerospace and Electronic Systems (TAES). This work has been submitted to the IEEE for possible publication

Nodal Capacity Expansion Planning with Flexible Large-Scale Load Siting

具有灵活大规模负荷选址的节点容量扩展规划

Tomas Valencia Zuluaga, Simon Pang, Jean-Paul Watson

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文提出将大规模负荷选址纳入随机节点电力系统容量扩展规划模型，同时优化发电、输电和储能扩展。通过将负荷分为不同可靠性要求的多个层级，考虑其运营灵活性，并利用两阶段随机混合整数优化问题和跨场景期望约束进行求解。

Comments Updated test cases and test cases description. Improved figures and literature review

SECAdvisor: a Tool for Cybersecurity Planning using Economic Models

SECAdvisor: 一种利用经济模型进行网络安全规划的工具

Muriel Figueredo Franco, Christian Omlin, Oliver Kamer, Eder John Scheid, Burkhard Stiller

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文提出SECAdvisor工具，通过经济模型帮助企业优化网络安全投资，评估风险，提供预算内保护方案，并比较不同防护方案的成本效益。

Comments 12 pages, 7 figures, 2 tables, 9 equations

Scale-Invariant Sampling in Multi-Arm Bandit Motion Planning for Object Extraction

多臂老虎机运动规划中的缩放不变采样用于物体提取

Servet B. Bayraktar, Andreas Orthey, Marc Toussaint

机构 * Technical University of Berlin（柏林技术大学） 纠错

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文提出一种缩放不变采样策略，用于多臂老虎机运动规划中的物体提取任务，通过生长-收缩搜索找到高熵采样尺度，并利用PCA确定提取方向，提高了8种3D物体提取场景的成功率。

Comments 19 pages, 5 figures. Accepted at WAFR 2026

Target-Bench: Can Video World Models Achieve Mapless Path Planning with Semantic Targets?

Target-Bench: 视频世界模型能否在语义目标下实现无地图路径规划？

Dingrui Wang, Zhihao Liang, Hongyuan Ye, Zhexiao Sun, Zhaowei Lu, Yuchen Zhang, Yuyu Zhao, Yuan Gao, Marvin Seegert, Finn Schäfer, Haotong Qin, Wei Li, Luigi Palmieri, Felix Jahncke, Mattia Piccinini, Johannes Betz

机构 * TUM（慕尼黑技术大学） ； Bosch AI Center（博世人工智能中心） ； ETH（苏黎世联邦理工学院） ； NJU（南京大学） 纠错

专题命中 规划决策 ：planning(title,abstract)

AI总结 Target-Bench首次评估视频世界模型的语义推理、空间估计和规划能力，通过450个机器人采集场景和5个互补指标揭示当前模型在语义推理与视觉生成间的显著差距。

Comments 19 pages

Robust Route Planning for Sidewalk Delivery Robots

面向人行道的鲁棒路径规划

Xing Tong, Michele D. Simoni

机构 * Division of Transport and Systems Analysis, KTH Royal Institute of Technology（交通与系统分析系，皇家理工学院） 纠错

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文研究了人行道配送机器人在动态环境中的鲁棒路径规划问题，通过模拟机器人、行人和障碍物的交互，结合鲁棒优化与仿真生成真实通行时间，评估不同机器人设计和环境条件下的效率。

Journal ref Transportation Research Part C: Emerging Technologies, 188(2026), 105670

Vectorizing Projection in Manifold-Constrained Motion Planning for Real-Time Whole-Body Control

流形约束运动规划中的向量投影：用于实时全身控制

Shrutheesh R Iyer, I-Chia Chang, Andrew Z. Liu, Yan Gu, Zachary Kingston

机构 * Department of Computer Science, Purdue University（普渡大学计算机科学系） ； School of Mechanical Engineering, Purdue University（普渡大学机械工程学院） 纠错

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文提出一种基于SIMD加速的流形约束运动规划器，通过并行化视角重新审视基于投影的约束满足方法，实现对复杂系统如人形机器人轨迹规划的实时约束满足。

Comments 8 pages, 8 figures, 3 tables. Under review

Weakly-supervised Learning for Physics-informed Neural Motion Planning via Sparse Roadmap

基于稀疏路图的弱监督物理引导神经运动规划

Ruiqi Ni, Yuchen Liu, Ahmed H. Qureshi

机构 * Department of Computer Science, Purdue University（普渡大学计算机科学系） 纠错

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文提出H-NTFields，结合稀疏路图的弱监督与物理引导PDE正则化，提升复杂环境中运动规划的鲁棒性和推理速度。

Smooth Feedback Motion Planning with Reduced Curvature

具有减少曲率的平滑反馈运动规划

Aref Amiri, Steven M. LaValle

机构 * Faculty of Information Technology and Electrical Engineering, University of Oulu（信息科技与电气工程学院，奥卢大学） 纠错

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文提出一种高效方法，通过系统对齐局部向量场和构造最大星形链，减少路径弯曲，提升机器人运动效率和控制效果。

Comments Accepted for publication in IEEE Robotics and Automation Letters

Safe and Nonconservative Contingency Planning for Autonomous Vehicles via Online Learning-Based Reachable Set Barriers

通过基于在线学习的可达集屏障实现自主车辆的安全非保守应急规划

Rui Yang, Lei Zheng, Shuzhi Sam Ge, Jun Ma

机构 * The Hong Kong University of Science and Technology（香港科学与技术大学） ； National University of Singapore（新加坡国立大学） ； Department of Electrical and Computer Engineering（电气与计算机工程系） 纠错

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文提出基于在线学习的实时应急轨迹优化框架，通过动态量化多模态HV不确定性并逐步细化其可达集，确保安全性和效率，在不确定环境下提升驾驶效率和乘客舒适度。

Comments 16 pages, 13 figures

Journal ref IEEE Trans. Control Syst. Technol., 2026, pp.1-16

Direct optimization of the probability of lesion origin in proton treatment planning for low-grade glioma patients

质子治疗低级别星形细胞瘤患者病变起源概率的直接优化

Tim Ortkamp, Habiba Sallem, Semi Harrabi, Martin Frank, Oliver Jäkel, Julia Bauer, Niklas Wahl

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文提出基于POLO模型的自动化治疗计划方法，通过整合POLO计算与优化，提高治疗计划的准确性，同时保持靶区覆盖度。

Comments 36 pages, 10 figures, 3 tables, partly already presented at PTCOG 62

Journal ref Med Phys. 2026;53:e70395

Ro-SLM: Onboard Small Language Models for Robot Task Planning and Operation Code Generation

Ro-SLM：机器人任务规划与操作代码生成的 onboard 小语言模型

Wenhao Wang, Yanyan Li, Long Jiao, Jiawei Yuan

机构 * Department of Computer & Information Science, University of Massachusetts Dartmouth（达特茅斯大学计算机与信息科学系） ； Department of Computer Science & Engineering, California State University San Marcos（加州州立大学桑马克斯分校计算机科学与工程系） 纠错

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文提出Ro-SLM框架，通过蒸馏大语言模型知识提升机器人任务规划与代码生成能力，实验证明其性能接近大语言模型。

Comments 25 pages, 2 figures, ACL 2026

Nemotron 3 Super: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning

Nemotron 3 Super：开放、高效的混合专家混合Mamba-Transformer模型用于代理推理

NVIDIA, :, Aakshita Chandiramani, Aaron Blakeman, Abdullahi Olaoye, Abhibha Gupta, Abhilash Somasamudramath, Abhinav Khattar, Adeola Adesoba, Adi Renduchintala, Adil Asif, Aditya Agrawal, Aditya Vavre, Ahmad Kiswani, Aishwarya Padmakumar, Ajay Hotchandani, Akanksha Shukla, Akhiad Bercovich, Aleksander Ficek, Aleksandr Shaposhnikov, Alex Gronskiy, Alex Kondratenko, Alex Neefus, Alex Steiner, Alex Yang, Alexander Bukharin, Alexander Young, Ali Hatamizadeh, Ali Taghibakhshi, Alina Galiautdinova, Alisa Liu, Alok Kumar, Ameya Sunil Mahabaleshwarkar, Amir Klein, Amit Zuker, Amnon Geifman, Anahita Bhiwandiwalla, Ananth Subramaniam, Andrew Tao, Anjaney Shrivastava, Anjulie Agrusa, Ankur Srivastava, Ankur Verma, Ann Guan, Anna Shors, Annamalai Chockalingam, Anubhav Mandarwal, Aparnaa Ramani, Arham Mehta, Arti Jain, Arun Venkatesan, Asha Anoosheh, Ashwath Aithal, Ashwin Poojary, Asif Ahamed, Asit Mishra, Asli Sabanci Demiroz, Asma Kuriparambil Thekkumpate, Atefeh Sohrabizadeh, Avinash Kaur, Ayush Dattagupta, Barath Subramaniam Anandan, Bardiya Sadeghi, Barnaby Simkin, Ben Lanir, Benedikt Schifferer, Benjamin Chislett, Besmira Nushi, Bilal Kartal, Bill Thiede, Bita Darvish Rouhani, Bobby Chen, Boris Ginsburg, Brandon Norick, Branislav Kisacanin, Brian Yu, Bryan Catanzaro, Buvaneswari Mani, Carlo del Mundo, Chankyu Lee, Chanran Kim, Chantal Hwang, Chao Ni, Charles Wang, Charlie Truong, Cheng-Ping Hsieh, Chenhan Yu, Chenjie Luo, Cherie Wang, Chetan Mungekar, Chintan Patel, Chris Alexiuk, Chris Holguin, Chris Wing, Christian Munley, Christopher Parisien, Chuck Desai, Chunyang Sheng, Collin Neale, Cyril Meurillon, Dakshi Kumar, Dan Gil, Dan Su, Dane Corneil, Daniel Afrimi, Daniel Burkhardt Eliuth Triana, Daniel Egert, Daniel Fatade, Daniel Lo, Daniel Rohrer, Daniel Serebrenik, Daniil Sorokin, Daria Gitman, Daria Levy, Darko Stosic, David Edelsohn, David Messina, David Mosallanezhad, David Tamok, Deena Donia, Deepak Narayanan, Devin O'Kelly, Dheeraj Peri, Dhruv Nathawani, Di Wu, Dima Rekesh, Dina Yared, Divyanshu Kakwani, Dmitry Konyagin Brandon Tuttle, Dong Ahn, Dongfu Jiang, Dorrin Poorkay, Douglas O'Flaherty, Duncan Riach, Dusan Stosic, Dustin Van Stee, Edgar Minasyan, Edward Lin, Eileen Peters Long, Elad Segal, Elena Lantz, Elena Lewis, Ellie Evans, Elliott Ning, Eric Chung, Eric Harper, Eric Pham-Hung, Eric W. Tramel, Erick Galinkin, Erik Pounds, Esti Etrog, Evan Briones, Evan Wu, Evelina Bakhturina, Evgeny Tsykunov, Ewa Dobrowolska, Farshad Saberi Movahed, Farzan Memarian, Fay Wang, Fei Jia, Felipe Soares, Felipe Vieira Frujeri, Feng Chen, Fengguang Lin, Ferenc Galko, Fortuna Zhang, Frankie Siino, Frida Hou, Gantavya Bhatt, Gargi Prasad, Geethapriya Venkataramani, Geetika Gupta, George Armstrong, Gerald Shen, Giulio Borghesi, Gordana Neskovic, Gorkem Batmaz, Grace Lam, Grace Wu, Greg Pauloski, Greyson Davis, Grigor Nalbandyan, Guoming Zhang, Guy Farber, Guyue Huang, Haifeng Qian, Haran Kumar Shiv Kumar, Harry Kim, Harsh Sharma, Hayate Iso, Hayley Ross, Herbert Hum, Herman Sahota, Hexin Wang, Himanshu Soni, Hiren Upadhyay, Huy Nguyen, Iain Cunningham, Ido Galil, Ido Shahaf, Igino Padovani, Igor Gitman, Igor Shovkun, Ikroop Dhillon, Ilya Loshchilov, Ingrid Kelly, Itamar Schen, Itay Levy, Ivan Moshkov, Izik Golan, Izzy Putterman, Jain Tu, Jan Baczek, Jan Kautz, Jane Polak Scowcroft, Janica Rosenberg, Jared Casper, Jarrod Pflum, Jason Grant, Jason Sewall, Jatin Mitra, Jeffrey Glick, Jenny Chen, Jesse Oliver, Jiacheng Xu, Jiafan Zhu, Jialin Song, Jian Zhang, Jiaqi Zeng, Jie Lou, Jill Milton, Jim Chow, Jimmy Zhang, Jinhang Choi, Jining Huang, Jocelyn Huang, Joel Caruso, Joey Conway, Joey Guman, Johan Jatko, John Kamalu, Johnny Greco, Jonathan Cohen, Jonathan Raiman, Joseph Jennings, Joyjit Daw, Juan Yu, Julio Tapia, Junkeun Yi, Jupinder Parmar, Jyothi Achar, Kari Briski, Kartik Mattoo, Katherine Cheung, Katherine Luna, Keith Wyss, Kevin Shih, Kezhi Kong, Khanh Nguyen, Khushi Bhardwaj, Kirill Buryak, Kirthi Shankar Sivamani, Konstantinos Krommydas, Kris Murphy, Krishna C. Puvvada, Krzysztof Pawelec, Kumar Anik, Laikh Tewari, Laya Sleiman, Leo Du, Leon Derczynski, Li Ding, Lilach Ilan, Lingjie Wu, Lizzie Wei, Luis Vega, Lun Su, Maarten Van Segbroeck, Maer Rodrigues de Melo, Magaret Zhang, Mahan Fathi, Makesh Narsimhan Sreedhar, Makesh Sreedhar, Makesh Tarun Chandran, Manuel Reyes Gomez, Maor Ashkenazi, Marc Cuevas, Marc Romeijn, Margaret Zhang, Mark Cai, Mark Gabel, Markus Kliegl, Martyna Patelka, Maryam Moosaei, Matthew Varacalli, Matvei Novikov, Mauricio Ferrato, Mehrzad Samadi, Melissa Corpuz, Meng Xin, Mengdi Wang, Mengru Wang, Meredith Price, Micah Schaffer, Michael Andersch, Michael Boone, Michael Evans, Michael Z Wang, Miguel Martinez, Mikail Khona, Mike Chrzanowski, Mike Hollinger, Mingyuan Ma, Minseok Lee, Mohammad Dabbah, Mohammad Shoeybi, Mostofa Patwary, Nabin Mulepati, Nader Khalil, Najeeb Nabwani, Nancy Agarwal, Nanthini Balasubramaniam, Narimane Hennouni, Narsi Kodukula, Natalie Hereth, Nathaniel Pinckney, Nave Assaf, Negar Habibi, Nestor Qin, Neta Zmora, Netanel Haber, Nick Reamaroon, Nickson Quak, Nidhi Bhatia, Nikhil Jukar, Nikki Pope, Nikolai Ludwig, Nima Tajbakhsh, Nir Ailon, Nirmal Juluru, Nirmalya De, Nowel Pitt, Oleg Rybakov, Oleksii Hrinchuk, Oleksii Kuchaiev, Olivier Delalleau, Oluwatobi Olabiyi, Omer Ullman Argov, Omri Almog, Omri Puny, Oren Tropp, Otavio Padovani, Ouye Xie, Parth Chadha, Pasha Shamis, Paul Gibbons, Pavlo Molchanov, Peter Belcak, Peter Jin, Pinky Xu, Piotr Januszewski, Pooya Jannaty, Prachi Shevate, Pradeep Thalasta, Pranav Prashant Thombre, Prasoon Varshney, Prerana Gambhir, Pritam Gundecha, Przemek Tredak, Qing Miao, Qiyu Wan, Quan Tran Minh, Rabeeh Karimi Mahabadi, Rachel Oberman, Rachit Garg, Rahul Kandu, Raina Zhong, Ran El-Yaniv, Ran Zilberstein, Rasoul Shafipour, Renee Yao, Renjie Pi, Richard Mazzarese, Richard Wang, Rick Izzo, Ridhima Singla, Rima Shahbazyan, Rishabh Garg, Ritika Borkar, Ritu Gala, Riyad Islam, Robert Clark, Robert Hesse, Roger Waleffe, Rohit Varma Kalidindi, Rohit Watve, Roi Koren, Ron Fan, Ruchika Kharwar, Ruisi Cai, Ruoxi Zhang, Russell J. Hewett, Ryan Prenger, Ryan Timbrook, Ryota Egashira, Sadegh Mahdavi, Sagar Singh Ashutosh Joshi, Sahil Modi, Samuel Kriman, Sandeep Pombra, Sanjay Kariyappa, Sanjeev Satheesh, Santiago Pombo, Saori Kaji, Satish Pasumarthi, Saurav Mishra, Saurav Muralidharan, Scott Hara, Sean Narenthiran, Sebastian Rogawski, Seonjin Na, Seonmyeong Bak, Sepehr Sameni, Seth Poulos, Shahar Mor, Shantanu Acharya, Shaona Ghosh Adam Lord, Sharath Turuvekere Sreenivas, Shaun Kotek, Shaya Gharghabi, Shelby Thomas, Sheng-Chieh Lin, Shibani Likhite, Shiqing Fan, Shiyang Chen, Shreya Gopal, Shrimai Prabhumoye, Shubham Pachori, Shubham Toshniwal, Shuo Zhang, Shuoyang Ding, Shyam Renjith, Shyamala Prayaga, Siddhartha Jain, Simeng Sun, Sirisha Rella, Sirshak Das, Smita Ithape, Sneha Harishchandra S, Somshubra Majumdar, Soumye Singhal, Sri Harsha Singudasu, Sriharsha Niverty, Stas Sergienko, Stefana Gloginic, Stefania Alborghetti, Stephen Ge, Stephen McCullough, Sugam Dipak Devare, Suguna Varshini Velury, Sukrit Rao, Sumeet Kumar Barua, Sunny Gai, Suseella Panguluri, Sushil Koundinyan, Swathi Patnam, Sweta Priyadarshi, Swetha Bhendigeri, Syeda Nahida Akter, Sylendran Arunagiri, Tailling Yuan, Talor Abramovich, Tan Bui, Tan Yu, Terry Kong, Thanh Do, Thomas Gburek, Thorgane Marques, Tiffany Moore, Tijmen Blankevoort, Tim Moon, Timothy Ma, Tiyasa Mitra, Tomasz Grzegorzek, Tomer Asida, Tomer Bar Natan, Tomer Keren, Tomer Ronen, Traian Rebedea, Trenton Starkey, Tugrul Konuk, Twinkle Vashishth, Tyler Condensa, Udi Karpas, Ushnish De, Vahid Noorozi, Vahid Noroozi, Vanshil Atul Shah, Veena Vaidyanathan, Venkat Srinivasan, Venmugil Elango, Victor Cui, Vijay Korthikanti, Vikas Mehta, Virginia Adams, Virginia Wu, Vitaly Kurin, Vitaly Lavrukhin, Vladimir Anisimov, Wan Seo, Wanli Jiang, Wasi Uddin Ahmad, Wei Du, Wei Ping, Wei-Ming Chen, Wendy Quan, Wenliang Dai, Wenwen Gao, Will Jennings, William Zhang, Xiaowei Ren, Xiaowen Xin, Xin Li, Yang Yu, Yangyi Chen, Yaniv Galron, Yashaswi Karnati, Yejin Choi, Yev Meyer, Yi-Fu Wu, Yian Zhang, Ying Lin, Yonatan Geifman, Yonggan Fu, Yoshi Suhara, Youngeun Kwon, Yuan Zhang, Yuki Huang, Zach Moshe, Zhilin Wang, Zhiyu Cheng, Zhongbo Zhu, Zhuolin Yang, Zihan Liu, Zijia Chen, Zijie Yan, Zuhair Ahmed

机构 * NVIDIA 纠错

专题命中 规划决策 ：agentic(title)；分类 cs.AI、cs.CL、cs.LG

AI总结 Nemotron 3 Super是首个采用NVFP4预训练、LatentMoE架构和MTP层加速推理的混合Mamba-Transformer模型，实现更高的推理吞吐量和准确率。

Goal-Conditioned Neural ODEs with Guaranteed Safety and Stability for Learning-Based All-Pairs Motion Planning

具有保证安全性和稳定性的目标条件神经ODEs用于基于学习的全对运动规划

Dechuan Liu, Ruigang Wang, Ian R. Manchester

机构 * Australian Centre for Robotics（澳大利亚机器人中心） ； School of Aerospace, Mechanical and Mechatronic Engineering（航空航天、机械与机电工程学院） 纠错

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文提出了一种基于学习的全对运动规划方法，通过双 Lipschitz 双射构造平滑的目标条件神经ODEs，理论结果表明该模型在任意目标位置下能保证全局指数稳定性与安全性，且提供了收敛速率、跟踪误差和向量场大小的显式界。

GraspSense: Physically Grounded Grasp and Grip Planning for a Dexterous Robotic Hand via Language-Guided Perception and Force Maps

GraspSense: 为灵活机械手提供基于语言引导感知和力图的抓取与握力规划

Elizaveta Semenyakina, Ivan Snegirev, Mariya Lezina, Miguel Altamirano Cabrera, Safina Gulyamova, Dzmitry Tsetserukou

机构 * Intelligent Space Robotics Laboratory, Skolkovo Institute of Science and Technology（斯科尔科沃科技学院智能空间机器人实验室） 纠错

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文提出一种基于力图的抓取与握力规划方法，通过物理建模和力图分析，使机械手能选择结构更坚固的接触区域并保持安全的抓取力。

Comments 6 pages, 4 figures, 4 tables. Minor non-semantic changes in the main scheme

Reliable and Real-Time Highway Trajectory Planning via Hybrid Learning-Optimization Frameworks

通过混合学习-优化框架实现可靠且实时的高速公路轨迹规划

Yujia Lu, Chong Wei, Lu Ma, Lounis Adouane

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文提出混合高速公路轨迹规划框架，结合学习方法的适应性和优化方法的正式安全保证，确保在多车交互复杂情况下实现高可靠性和实时性。

Towards Designing for Resilience: Community-Centered Deployment of an AI Business Planning Tool in a Small Business Center

迈向韧性设计：在小型企业中心部署一个AI业务规划工具的社区中心化方法

Quentin Romero Lauro, Aakash Gautam, Yasmine Kotturi

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文探讨了在资源有限社区中，通过社区中心化设计部署AI业务规划工具BizChat，研究创业者如何通过集体AI素养发展建立韧性，发现AI工具在降低融资门槛的同时也引发了对规划本质的质疑。

Comments 17 pages, accepted to CHI 2026

Motion planning and approximate controllability of a moving cantilever beam with a tip-mass

带有末端质量的移动悬臂梁的运动规划与近似可控性

Soham Chatterjee, Aman Batra, Vivek Natarajan

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文研究了带有末端质量的悬臂梁模型在给定时间区间内从初始状态转移到最终状态的运动规划问题，并利用生成函数方法证明了该模型的近似可控性。

Comments 14 pages, 8 figures

SBAMP: Sampling Based Adaptive Motion Planning

基于采样的自适应运动规划：SBAMP

Shreyas Raorane, Kabir Ram Puri, Anh-Quan Pham

机构 * General Robotics, Automation, Sensing and Perception (GRASP) Laboratory, University of Pennsylvania（宾夕法尼亚大学通用机器人、自动化、感知与感知（GRASP）实验室） 纠错

专题命中 规划决策 ：planning(title,abstract)

AI总结 SBAMP结合RRT*全局规划与在线Lyapunov稳定的SEDS控制器，实现动态环境下的稳定实时适应与全局路径保持。

A New Approach to Motion Planning in 3D for a Dubins Vehicle: Special Case on a Sphere

在球面上Dubins车辆3D运动规划的新方法：特殊情形

Deepak Prakash Kumar, Swaroop Darbha, Satyanarayana Gupta Manyam, David Casbeer

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文提出了一种适用于空中车辆的3D运动规划新模型，研究了曲率受限车辆在球面表面的运动规划问题，推导了最小转弯半径车辆的最优路径，并扩展了最优路径的范围。

PlanGuard: Defending Agents against Indirect Prompt Injection via Planning-based Consistency Verification

PlanGuard：通过基于规划的一致性验证防御代理 against 间接提示注入

Guangyu Gong, Zizhuang Deng

专题命中 规划决策 ：planning(title)；agent(abstract)

AI总结 本文提出PlanGuard，一种基于上下文隔离的无训练防御框架，通过规划器生成有效动作集和分层验证机制，有效防御间接提示注入攻击，实验显示攻击成功率从72.8%降至0%。

Joint UAV-UGV Positioning and Trajectory Planning via Meta A3C for Reliable Emergency Communications

通过元A3C实现UAV-UGV的联合定位与轨迹规划以实现可靠的应急通讯

Ndagijimana Cyprien, Mehdi Sookhak, Hosein Zarini, Chandra N Sekharan, Mohammed Atiquzzaman

机构 * Department of Computer Science, Texas A&M University-Corpus Christi（德克萨斯农工大学科珀斯克里斯蒂分校计算机科学系） ； School of Computer Science, University of Oklahoma（俄克拉荷马大学计算机科学学院） 纠错

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文提出了一种基于元A3C的UAV-UGV联合定位与轨迹规划框架，通过道路图建模UGV移动并优化总速率问题，实验表明其在吞吐量和执行速度上优于A3C和DDPG。

Journal ref Proceedings of the IEEE Global Communications Conference (GLOBECOM), 2025, Taipei, Taiwan, Dec. 2025

Exact Bayesian Planning for Simple Step-Stress Accelerated Life Testing with Competing Risks

简单步应力加速寿命测试中竞争风险的精确贝叶斯规划

Kiran Prajapat

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文提出一种贝叶斯框架，用于规划简单步应力加速寿命测试，考虑两个独立竞争失效模式。通过累积暴露模型和对数线性应力-寿命关系连接不同应力水平下的失效时间分布，采用非渐近方法优化p分位数的预后方差。

Comments 37 pages, 8 figures

One Interface, Many Robots: Unified Real-Time Low-Level Motion Planning for Collaborative Arms

一个接口，多种机器人：面向协作臂的统一实时低级运动规划

Yue Feng, Weicheng Huang, I-Ming Chen

机构 * Robotics Research Center (RRC), Nanyang Technological University（南洋理工大学机器人研究中心） ； WinGs Robotics LLC（WinGs 机器人有限责任公司） 纠错

专题命中 规划决策 ：planning(title,abstract)

AI总结 本文提出一个统一的实时低级运动规划接口，用于协作机器人臂，旨在提高在异构硬件平台上的应用性和可移植性。通过n次多项式插值与二次规划求解器结合，生成平滑连续可微的轨迹。在三个不同场景中验证了方法的可靠性、通用性和易用性。