Tootfinder

Design, fabrication and control of a cable-driven parallel robot
Dhruv Sorathiya, Sarthak Sahoo, Vivek Natarajan
https://arxiv.org/abs/2506.18526 https://

Design, fabrication and control of a cable-driven parallel robot
In cable driven parallel robots (CDPRs), the payload is suspended using a network of cables whose length can be controlled to maneuver the payload within the workspace. Compared to rigid link robots, CDPRs provide better maneuverability due to the flexibility of the cables and consume lesser power due to the high strength-to-weight ratio of the cables. However, amongst other things, the flexibility of the cables and the fact that they can only pull (and not push) render the dynamics of CDPRs co…

Testing the Lense-Thirring Precession Origin of the QPO in Swift J1727.8$-$1613
Ruican Ma, Chris Done, Aya Kubota
https://arxiv.org/abs/2506.18857 https://…

Testing the Lense-Thirring Precession Origin of the QPO in Swift J1727.8$-$1613
We present a comprehensive spectral and timing analysis of the newly discovered black hole transient Swift J1727.8$-$1613, based on broadband (2$-$150 keV) observations from $Insight$-HXMT during its 2023 outburst. We use the flexible, energy-conserving SSsed model to model both the outer disc and inner, complex Comptonisation, using the expected disc emissivity to constrain the inner disc radius, $r_{cor}$. This decreases from 45 $R_{\rm g}$ to 9 $R_{\rm g}$ duing the transition from the hard …

I've been 'working-from-home' for 30yrs. Microsoft has enabled WFH since I joined in 1995 via Remote Access Services/RAS - over dial-up or ISDN.
This was a Microsoft strength: No one was ever out of touch or "off work hours". We all had laptops, cellphones, pagers, MCI concall accounts & ISDN lines at home. Everyone was "on" all the time. And we liked it.
✅ Flexible Work Was The Promise. The Infinite Workday Is The Reality. - Fobes

Flexible Work Was The Promise. The Infinite Workday Is The Reality.
New research from Microsoft reveals the rise of the infinite workday. Find out why flexibility is not enough and how to fix our broken rhythm on the clock.

VLM-Empowered Multi-Mode System for Efficient and Safe Planetary Navigation
Sinuo Cheng, Ruyi Zhou, Wenhao Feng, Huaiguang Yang, Haibo Gao, Zongquan Deng, Liang Ding
https://arxiv.org/abs/2506.16703

VLM-Empowered Multi-Mode System for Efficient and Safe Planetary Navigation
The increasingly complex and diverse planetary exploration environment requires more adaptable and flexible rover navigation strategy. In this study, we propose a VLM-empowered multi-mode system to achieve efficient while safe autonomous navigation for planetary rovers. Vision-Language Model (VLM) is used to parse scene information by image inputs to achieve a human-level understanding of terrain complexity. Based on the complexity classification, the system switches to the most suitable naviga…

This https://arxiv.org/abs/2310.01147 has been replaced.
link: https://scholar.google.com/scholar?q=a

Optimizing Symbol Visibility through Displacement
In information visualization, the position of symbols often encodes associated data values. When visualizing data elements with both a numerical and a categorical dimension, positioning in the categorical axis admits some flexibility. This flexibility can be exploited to reduce symbol overlap, and thereby increase legibility. In this paper, we initialize the algorithmic study of optimizing symbol legibility via a limited displacement of the symbols. Specifically, we consider closed unit square …

What's in the Box? Reasoning about Unseen Objects from Multimodal Cues
Lance Ying, Daniel Xu, Alicia Zhang, Katherine M. Collins, Max H. Siegel, Joshua B. Tenenbaum
https://arxiv.org/abs/2506.14212

What's in the Box? Reasoning about Unseen Objects from Multimodal Cues
People regularly make inferences about objects in the world that they cannot see by flexibly integrating information from multiple sources: auditory and visual cues, language, and our prior beliefs and knowledge about the scene. How are we able to so flexibly integrate many sources of information to make sense of the world around us, even if we have no direct knowledge? In this work, we propose a neurosymbolic model that uses neural networks to parse open-ended multimodal inputs and then applie…

FCRF: Flexible Constructivism Reflection for Long-Horizon Robotic Task Planning with Large Language Models
Yufan Song, Jiatao Zhang, Zeng Gu, Qingmiao Liang, Tuocheng Hu, Wei Song, Shiqiang Zhu
https://arxiv.org/abs/2507.14975

FCRF: Flexible Constructivism Reflection for Long-Horizon Robotic Task Planning with Large Language Models
Autonomous error correction is critical for domestic robots to achieve reliable execution of complex long-horizon tasks. Prior work has explored self-reflection in Large Language Models (LLMs) for task planning error correction; however, existing methods are constrained by inflexible self-reflection mechanisms that limit their effectiveness. Motivated by these limitations and inspired by human cognitive adaptation, we propose the Flexible Constructivism Reflection Framework (FCRF), a novel Ment…

Data-Driven MPC with Data Selection for Flexible Cable-Driven Robotic Arms
Huayue Liang, Yanbo Chen, Hongyang Cheng, Yanzhao Yu, Shoujie Li, Junbo Tan, Xueqian Wang, Long Zeng
https://arxiv.org/abs/2507.15677

Data-Driven MPC with Data Selection for Flexible Cable-Driven Robotic Arms
Flexible cable-driven robotic arms (FCRAs) offer dexterous and compliant motion. Still, the inherent properties of cables, such as resilience, hysteresis, and friction, often lead to particular difficulties in modeling and control. This paper proposes a model predictive control (MPC) method that relies exclusively on input-output data, without a physical model, to improve the control accuracy of FCRAs. First, we develop an implicit model based on input-output data and integrate it into an MPC o…

Gaze-supported Large Language Model Framework for Bi-directional Human-Robot Interaction
Jens V. R\"uppel, Andrey Rudenko, Tim Schreiter, Martin Magnusson, Achim J. Lilienthal
https://arxiv.org/abs/2507.15729

Gaze-supported Large Language Model Framework for Bi-directional Human-Robot Interaction
The rapid development of Large Language Models (LLMs) creates an exciting potential for flexible, general knowledge-driven Human-Robot Interaction (HRI) systems for assistive robots. Existing HRI systems demonstrate great progress in interpreting and following user instructions, action generation, and robot task solving. On the other hand, bi-directional, multi-modal, and context-aware support of the user in collaborative tasks still remains an open challenge. In this paper, we present a gaze- …