Microsoft announces US$10B AI investment plan in Japan - MSN
Microsoft announces US$10B AI investment plan in Japan MSN
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IA-TIGRIS: An Incremental and Adaptive Sampling-Based Planner for Online Informative Path Planning
arXiv:2502.15961v3 Announce Type: replace Abstract: Planning paths that maximize information gain for robotic platforms has wide-ranging applications and significant potential impact. To effectively adapt to real-time data collection, informative path planning must be computed online and be responsive to new observations. In this work, we present IA-TIGRIS (Incremental and Adaptive Tree-based Information Gathering Using Informed Sampling), which is an incremental and adaptive sampling-based informative path planner designed for real-time onboard execution. Our approach leverages past planning efforts through incremental refinement while continuously adapting to updated belief maps. We additionally present detailed implementation and optimization insights to facilitate real-world deployment
ThinkGrasp: A Vision-Language System for Strategic Part Grasping in Clutter
arXiv:2407.11298v2 Announce Type: replace Abstract: Robotic grasping in cluttered environments remains a significant challenge due to occlusions and complex object arrangements. We have developed ThinkGrasp, a plug-and-play vision-language grasping system that makes use of GPT-4o's advanced contextual reasoning for heavy clutter environment grasping strategies. ThinkGrasp can effectively identify and generate grasp poses for target objects, even when they are heavily obstructed or nearly invisible, by using goal-oriented language to guide the removal of obstructing objects. This approach progressively uncovers the target object and ultimately grasps it with a few steps and a high success rate. In both simulated and real experiments, ThinkGrasp achieved a high success rate and significantly
How Leg Stiffness Affects Energy Economy in Hopping
arXiv:2501.03971v2 Announce Type: replace Abstract: In the fields of robotics and biomechanics, the integration of elastic elements such as springs and tendons in legged systems has long been recognized for enabling energy-efficient locomotion. Yet, a significant challenge persists: designing a robotic leg that perform consistently across diverse operating conditions, especially varying average forward speeds. It remains unclear whether, for such a range of operating conditions, the stiffness of the elastic elements needs to be varied or if a similar performance can be obtained by changing the motion and actuation while keeping the stiffness fixed. This work explores the influence of the leg stiffness on the energy efficiency of a monopedal robot through an extensive parametric study of it
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Temple University Japan Advances Academic Offerings with Launch of Bachelor of Science in Artificial Intelligence for Fall 2026 - TUJ News
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Washington launches export initiative to ensure ‘future of AI is led by the United States’
The US government has unveiled an AI export initiative designed to cement American technological leadership while countering China’s growing influence in the sector. Washington is inviting US companies to form “preset” consortiums to offer full-stack artificial intelligence solutions around the world. Applications will be accepted until the end of June, the International Trade Administration (ITA), an agency under the US Department of Commerce, said in a news release issued on Wednesday. The...
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