robotics
PulseAugur coverage of robotics — every cluster mentioning robotics across labs, papers, and developer communities, ranked by signal.
- used by World Models 80%
- instance of ScienceCast 70%
- instance of Gotit.pub 70%
- used by Gotit.pub 70%
- instance of CORE Recommender 70%
- used by CORE Recommender 70%
- instance of CatalyzeX Code Finder for Papers 70%
- affiliated with autonomous driving 70%
- developed Gotit.pub 70%
- developed DagsHub 70%
- developed ScienceCast 70%
- used by ScienceCast 70%
- 2026-07-16 research_milestone Researchers introduced RoboTTT, a robot model and training recipe that scales visuomotor context to 8K timesteps, enabling new capabilities like one-shot imitation and improved performance on long-horizon tasks. source
18 day(s) with sentiment data
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New framework ActiveScale enhances robot active perception
Researchers have developed ActiveScale, a new framework designed to improve active perception in robots. This system integrates model, data, and hardware advancements to enable robots to reason across changing viewpoint…
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Multi-humanoid robots learn cooperative object transport via decentralized control
Researchers have developed a decentralized object-centric control system for multi-humanoid robots to cooperatively pick up and transport objects of varying properties. The approach utilizes a gripperless bimanual pinch…
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AI and Robotics Accelerate Manufacturing DX; Autonomous Agents Automate Computer Use
Artificial intelligence and robotics are driving significant advancements in manufacturing digitalization, with real-world case studies and performance metrics highlighting key success factors and challenges. Concurrent…
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Nvidia exec: Robots need a ChatGPT moment, data gap is key hurdle
Nvidia executive Les Karpas will discuss the challenges and opportunities in physical AI and robotics at TechCrunch Disrupt 2026. He plans to explain why robotics has not yet experienced a "ChatGPT moment" comparable to…
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Capgemini CEO: Agility and human-centricity key for AI adoption
Aiman Ezzat, CEO of Capgemini, emphasizes that agility and a human-centric approach are crucial for businesses navigating the evolving AI landscape. He advises against excessive upfront investment in AI, advocating inst…
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Robotics research introduces factor graph for deformable object reconstruction
Researchers have developed a new framework for estimating the state of deformable objects, crucial for robotics and simulation. This method utilizes a factor graph to probabilistically update a tetrahedral mesh, integra…
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Robotics framework tackles terrain adaptation and catastrophic forgetting
Researchers have developed a new continual learning framework for traversability prediction in robotics. This framework aims to help robots adapt to new terrains without forgetting previously learned environments, a com…
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New framework evaluates SLAM system robustness under adverse conditions
Researchers have developed SLAM Adversarial Lab (SAL), a modular framework designed to evaluate the robustness of visual Simultaneous Localization and Mapping (SLAM) systems under adverse conditions like fog and rain. S…
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Vision-Language Models Show Promise for Robotic Fruit Harvesting
Researchers have developed a new benchmark to evaluate vision-language models (VLMs) for their ability to perform zero-shot multi-arm robotic fruit harvesting. The study compared a VLM-based planning pipeline against a …
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Robotics research introduces outcome-based representation learning
Researchers have developed a novel method for learning manipulation-sufficient representations in robotics, focusing on action outcomes rather than dense geometric states. This approach utilizes an action-conditioned ou…
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New framework optimizes robot counterweights for task distributions
Researchers have developed a new framework for designing passive counterweights in serial manipulators, optimizing them for specific task distributions rather than single poses. The proposed method explicitly incorporat…
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New method steers generative robot policies with prioritized objectives
Researchers have developed a novel method to steer pre-trained generative robot policies at inference time, allowing them to adhere to prioritized deployment objectives without altering the policy's weights. This approa…
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New method improves robot learning from human feedback
A new research paper proposes IMPLIED, a method for improving preference learning in human-robot collaboration. Traditional methods rely on fixed rules to infer human preferences, but this paper shows that human-provide…
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ReWeight framework improves robot learning with human demonstration data
Researchers have developed ReWeight, a novel framework designed to enhance the post-training of vision-language-action (VLA) models for robotics. This method addresses the challenge of costly robot data collection by le…
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New variable horizon method enhances multi-drone collision avoidance
Researchers have developed a novel conflict-predictive variable horizon approach for multi-drone distributed model predictive control. This method allows each drone to dynamically adjust its prediction horizon based on …
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AI Builder vs. Non-Builder Gap Noted at Amazon Robotics
A co-blogger has observed a significant gap between AI builders and non-builders within Amazon Robotics. This disparity has implications for the development of complex, integrated systems. A new post on Robot Girl Gang …
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Digital Divide Data opens AI & robotics center in India, creating jobs
Digital Divide Data (DDD), a social enterprise focused on AI and data services, has opened a new Global Capability Center (GCC) in Dehradun, India. This center will specialize in physical AI, robotics, and generative AI…
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New multi-vehicle dataset released for autonomous driving research
A new multi-vehicle dataset has been released, featuring synchronized data from cameras, LiDAR, and radar sensors, along with scanned 3D models of vehicles. This dataset aims to provide a highly detailed reference for a…
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New frameworks enhance robot policies with flow matching and safety constraints · 4 sources tracked
Researchers have developed several new frameworks for improving flow-based policies in reinforcement learning, particularly for robotics. These methods aim to address challenges like multimodal action distributions and …
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Guide to Imitation Learning for Robotics Released
This article provides a guide to implementing imitation learning (IL) for robotics, focusing on vision-based policies trained from scratch. It contrasts IL with classic explicit policies and reinforcement learning, high…