Tootfinder

Pittsburgh-based Gecko Robotics, which makes robots to inspect infrastructure, raised a $125M Series D at a $1.25B valuation, up from $633M in December 2023 (Ian Thomas/CNBC)
https://www.cnbc.com/2025/06/12/gecko-robotics-…

Gecko Robotics raises $125 million in deal valuing critical infrastructure startup over $1 billion
Gecko Robotics, which uses robots and AI to inspect and monitor critical infrastructure, has raised a $125 million, bringing its valuation to $1.25 billion.

from my link log —
ai.robots.txt: A list of AI agents and robots to block.
https://github.com/ai-robots-txt/ai.robots.txt
saved 2025-01-16

GitHub - ai-robots-txt/ai.robots.txt: A list of AI agents and robots to block.
A list of AI agents and robots to block. Contribute to ai-robots-txt/ai.robots.txt development by creating an account on GitHub.

Trotzdem beliebt: Waymo-Robotaxis sind teurer, kommen später als die Konkurrenz
Die autonomen Taxis von Waymo sorgen zumindest bislang nicht für einen Preisverfall bei Taxifahrten in Los Angeles. Laut einer Studie sind sie merklich teurer.

If anything, my OP was insufficiently derogatory.
#TeslaTakedown
https://electrek.co/2025/07/14/tesla-penis-shaped-robotaxi-expansion-illustrates-unserious-business/

Robotic Calibration Based on Haptic Feedback Improves Sim-to-Real Transfer
Juraj Gavura, Michal Vavrecka, Igor Farkas, Connor Gade
https://arxiv.org/abs/2507.08572

Robotic Calibration Based on Haptic Feedback Improves Sim-to-Real Transfer
When inverse kinematics (IK) is adopted to control robotic arms in manipulation tasks, there is often a discrepancy between the end effector (EE) position of the robot model in the simulator and the physical EE in reality. In most robotic scenarios with sim-to-real transfer, we have information about joint positions in both simulation and reality, but the EE position is only available in simulation. We developed a novel method to overcome this difficulty based on haptic feedback calibration, us…

Never mind the dummy,
The Robotaxi also failed to stop for the stop sign.
Nice hit and run afterwards, though.
https://bsky.app/profile/carlquintanilla.bsky.social/post/3lridgcwvvc2n

Waymo temporarily limits service in SF, Austin, and Atlanta, and stops service in LA, as US cities prepare for protests against federal immigration policies (Aarian Marshall/Wired)
https://www.wired.com/story/ahead-of-protests-waymo-adjusts…

Ahead of Protests, Waymo Scales Back Robotaxi Service Nationwide
A week after five robot cars were burned in Los Angeles, the Google sister company isn’t taking risks.

Learning Robust Motion Skills via Critical Adversarial Attacks for Humanoid Robots
Yang Zhang, Zhanxiang Cao, Buqing Nie, Haoyang Li, Yue Gao
https://arxiv.org/abs/2507.08303

Learning Robust Motion Skills via Critical Adversarial Attacks for Humanoid Robots
Humanoid robots show significant potential in daily tasks. However, reinforcement learning-based motion policies often suffer from robustness degradation due to the sim-to-real dynamics gap, thereby affecting the agility of real robots. In this work, we propose a novel robust adversarial training paradigm designed to enhance the robustness of humanoid motion policies in real worlds. The paradigm introduces a learnable adversarial attack network that precisely identifies vulnerabilities in motio…

The dollar sank to its lowest level in more than three years on Thursday
and the FTSE 100 closed at a record high as Donald Trump’s latest trade threats and the weakening economy appeared to bring forward interest rate cuts by the Federal Reserve.
Foreign exchange traders sold the dollar in favour of the yen and the euro,
which both climbed by about 1% against the US currency to leave it almost 10% down on its value against a basket of currencies since the beginning of the …

CL3R: 3D Reconstruction and Contrastive Learning for Enhanced Robotic Manipulation Representations
Wenbo Cui, Chengyang Zhao, Yuhui Chen, Haoran Li, Zhizheng Zhang, Dongbin Zhao, He Wang
https://arxiv.org/abs/2507.08262

CL3R: 3D Reconstruction and Contrastive Learning for Enhanced Robotic Manipulation Representations
Building a robust perception module is crucial for visuomotor policy learning. While recent methods incorporate pre-trained 2D foundation models into robotic perception modules to leverage their strong semantic understanding, they struggle to capture 3D spatial information and generalize across diverse camera viewpoints. These limitations hinder the policy's effectiveness, especially in fine-grained robotic manipulation scenarios. To address these challenges, we propose CL3R, a novel 3D pre-tra…