Tootfinder

Energy Aware Camera Location Search Algorithm for Increasing Precision of Observation in Automated Manufacturing
Rongfei Li, Francis Assadian
https://arxiv.org/abs/2506.10251

Energy Aware Camera Location Search Algorithm for Increasing Precision of Observation in Automated Manufacturing
Visual servoing technology has been well developed and applied in many automated manufacturing tasks, especially in tools' pose alignment. To access a full global view of tools, most applications adopt eye-to-hand configuration or eye-to-hand/eye-in-hand cooperation configuration in an automated manufacturing environment. Most research papers mainly put efforts into developing control and observation architectures in various scenarios, but few of them have discussed the importance of the camera…

😶‍🌫️ Generating real-time detailed ground visualisations from sparse aerial point clouds
#3d #xr

Generating real-time detailed ground visualisations from sparse aerial point clouds
Building realistic wide scale outdoor 3D content with sufficient visual quality to observe at walking eye level or from driven vehicles is often carried out by large teams of artists skilled in modelling, texturing, material shading and lighting, which typically leads to both prohibitive costs and reduced accuracy honoring the variety of real world ground truth landscapes. In our proposed method, we define a process to automatically amplify real-world scanned data and render real-time in animat…

Automatic Failure Attribution and Critical Step Prediction Method for Multi-Agent Systems Based on Causal Inference
Guoqing Ma, Jia Zhu, Hanghui Guo, Weijie Shi, Jiawei Shen, Jingjiang Liu, Yidan Liang
https://arxiv.org/abs/2509.08682

Automatic Failure Attribution and Critical Step Prediction Method for Multi-Agent Systems Based on Causal Inference
Multi-agent systems (MAS) are critical for automating complex tasks, yet their practical deployment is severely hampered by the challenge of failure attribution. Current diagnostic tools, which rely on statistical correlations, are fundamentally inadequate; on challenging benchmarks like Who\&When, state-of-the-art methods achieve less than 15\% accuracy in locating the root-cause step of a failure. To address this critical gap, we introduce the first failure attribution framework for MAS groun…

In the Air - Inside of the Window ✈️ 👩‍✈️
在空中 - 窗内 ✈️ 👩‍✈️
📷 Nikon FE
🎞️FOMAPAN Action 400
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

now i really want to try Cheddar Bay biscuits https://mas.to/@carnage4life/114830335171951140

Learning-Augmented Model-Based Multi-Robot Planning for Time-Critical Search and Inspection Under Uncertainty
Abhish Khanal, Joseph Prince Mathew, Cameron Nowzari, Gregory J. Stein
https://arxiv.org/abs/2507.06129

Learning-Augmented Model-Based Multi-Robot Planning for Time-Critical Search and Inspection Under Uncertainty
In disaster response or surveillance operations, quickly identifying areas needing urgent attention is critical, but deploying response teams to every location is inefficient or often impossible. Effective performance in this domain requires coordinating a multi-robot inspection team to prioritize inspecting locations more likely to need immediate response, while also minimizing travel time. This is particularly challenging because robots must directly observe the locations to determine which o…

"Volume Two: Thank You For Your Patience" is one of my recent favorite albums. Milwaukee's the Beat Index clearly had a blast making "an album of on-hold music for automated phone systems." You really need to listen to the whole album - it's sonically on point, damn catchy, and brutally funny (the endlessly repeating tri-tone at the end of the full album "Telesthesia Mix" makes me wanna cry every time).
"Caught in a Lie (Hotline Mix)" (20…

#Neurotypicals: You need to be bored. Next time you go to the gym, don't listen to that podcast. Just try to be in your head for a while. Maybe you'll think about the meaning of life, and maybe you'll figure it out.
My #ADHD brain trying to unload the dishwasher without a podcast: Hey, Remember the intro to Clifford the Big Red Dog? That song? You sort of paid attention to it for a few seconds while our kid was watching it. I remember those 5 seconds. Let's sing that intro... just that first part though. We're just going to keep doing that, over and over, hundreds of times in a row.
Neurotypicals: People don't like to be bored. People will give themselves electric shocks to not be bored. They don't want to think about the big questions
My ADHD brain, still trying to unload the dishwasher without a podcast: ♪ Welcome to Birdwell island, Sun and the sky is smilin' ♪ ♪ ♪ Welcome to Birdwell island, Sun and the sky is smilin' ♪ ♪ ♪ Welcome to Birdwell island, Sun and the sky is smilin' ♪ ♪ ♪ Welcome to Birdwell island, Sun and the sky is smilin' ♪ ♪ ♪ Welcome to Birdwell island, Sun and the sky is smilin' ♪ ♪ ♪ Welcome to Birdwell island, Sun and the sky is smilin' ♪ ♪ ♪ Welcome to Birdwell island, Sun and the sky is smilin' ♪ ♪ ♪ Welcome to Birdwell island, Sun and the sky is smilin' ♪ ♪ ♪ Welcome to Birdwell island, Sun and the sky is smilin' ♪ ♪ ♪ Welcome to Birdwell island, Sun and the sky is smilin' ♪ ♪
https://youtu.be/orQKfIXMiA8

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners
Katsuhiko Yamamoto, Koichi Miyazaki
https://arxiv.org/abs/2507.05729

Non-Intrusive Binaural Speech Intelligibility Prediction Using Mamba for Hearing-Impaired Listeners
Speech intelligibility prediction (SIP) models have been used as objective metrics to assess intelligibility for hearing-impaired (HI) listeners. In the Clarity Prediction Challenge 2 (CPC2), non-intrusive binaural SIP models based on transformers showed high prediction accuracy. However, the self-attention mechanism theoretically incurs high computational and memory costs, making it a bottleneck for low-latency, power-efficient devices. This may also degrade the temporal processing of binaural…

Pointing-Guided Target Estimation via Transformer-Based Attention
Luca M\"uller, Hassan Ali, Philipp Allgeuer, Luk\'a\v{s} Gajdo\v{s}ech, Stefan Wermter
https://arxiv.org/abs/2509.05031

Pointing-Guided Target Estimation via Transformer-Based Attention
Deictic gestures, like pointing, are a fundamental form of non-verbal communication, enabling humans to direct attention to specific objects or locations. This capability is essential in Human-Robot Interaction (HRI), where robots should be able to predict human intent and anticipate appropriate responses. In this work, we propose the Multi-Modality Inter-TransFormer (MM-ITF), a modular architecture to predict objects in a controlled tabletop scenario with the NICOL robot, where humans indicate…