IROS

Thinker: A vision-language foundation model for embodied intelligence

Thinker：一个用于具身智能的视觉-语言基础模型

Baiyu Pan, Daqin Luo, Junpeng Yang, Jiyuan Wang, Yixuan Zhang, Hailin Shi, Jichao Jiao

AI总结 Thinker通过构建大规模数据集和改进输入方式，在机器人感知与推理任务中实现了最先进的性能。

Comments IROS 2025, 4 pages, 3 figures

Multi-Step Deep Koopman Network (MDK-Net) for Vehicle Control in Frenet Frame

多步深度Koopman网络（MDK-Net）用于Frenet框架中的车辆控制

Mohammad Abtahi, Mahdis Rabbani, Armin Abdolmohammadi, Shima Nazari

机构 * Mechanical and Aerospace Engineering of University of California, Davis（加州大学戴维斯分校机械与航空航天工程学院） 纠错

AI总结 本文提出了一种基于深度学习的Koopman建模方法，用于在Frenet框架内实现车辆控制，通过多步深度Koopman网络提升路径规划和跟随的控制性能。

Comments This work has been submitted for IROS 2025 conference

Journal ref 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Designing Underactuated Graspers with Dynamically Variable Geometry Using Potential Energy Map Based Analysis

设计具有动态可变几何结构的欠驱动夹具：基于能量图的分析

C. L. Yako, Shenli Yuan, J. Kenneth Salisbury

机构 * Stanford Artificial Intelligence Lab (SAIL)（斯坦福人工智能实验室（SAIL）） ； Stanford University（斯坦福大学） 纠错

AI总结 本文提出基于能量图的欠驱动夹具设计方法，通过引入摩擦力分析，实现动态可变几何结构以适应不同尺寸物体的抓取需求。

Comments This is an updated version of my original paper (with the same title) published in IROS 2022. Parts of this work were refined or corrected in Chapter 3 of my dissertation, Good Vibrations: Toward Vibration-Based Robotic In-Hand Manipulation (DOI: 10.25740/mm182vq8220), and many of those changes have been incorporated here