Well structured visual representations can make robot learning faster and can improve generalization. In this paper, we study how we can acquire effective object-centric representations for robotic manipulation tasks without human labeling by using a...
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Jan 14, 2026 · Intuitive (Nasdaq: ISRG), headquartered in Sunnyvale, California, is a global leader in minimally invasive care and the pioneer of robotic-assisted surgery. Our technologies include the da …
Discover how Intuitive is advancing what’s possible in minimally invasive care with its innovative da Vinci surgical and Ion endoluminal systems.
Whole-body Control (WBC) has emerged as an important framework in locomotion control for legged robots. However, most of WBC frameworks fail to generalize beyond rigid terrains. Legged locomotion over soft terrain is difficult due to the presence of...
Our extensive testing process involves weeks or months of research, combining expert insights and consumer feedback. From creating obstacle courses for robot vacuums to fireproof safe tests, we …
Box/cabinet scenarios with stacked objects pose significant challenges for robotic motion due to visual occlusions and constrained free space. Traditional collision-free trajectory planning methods often fail when no collision-free paths exist, and m...
This paper introduces a learning-based framework for robot adaptive manipulating the object with a revolute joint in unstructured environments. We concentrate our discussion on various cabinet door opening tasks. To improve the performance of Deep Re...
We address the important problem of generalizing robotic rearrangement to clutter without any explicit object models. We first generate over 650K cluttered scenes - orders of magnitude more than prior work - in diverse everyday environments, such as...
In this paper, we explore how we can build upon the data and models of Internet images and use them to adapt to robot vision without requiring any extra labels. We present a framework called Self-supervised Embodied Active Learning (SEAL). It utilize...
Following the impressive capabilities of in-context learning with large transformers, In-Context Imitation Learning (ICIL) is a promising opportunity for robotics. We introduce Instant Policy, which learns new tasks instantly (without further trainin...
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A classic task in robotics is tracking a target in the external environment. There are several well-documented approaches to this problem. This paper presents a novel approach to this problem using infrared time of flight sensors. The use of infrared...
Mr. Robot. Henig was a main cast member playing the protagonist role of Julian in the second season of the USA Network drama The Sinner, and alongside
Gameplay Spare Parts is a platform game featuring robots. Spare Parts is a platform game. It features local and online cooperative gameplay, and players can drop in and out on the fly. [2] The game â¦
Following its success in natural language processing and computer vision, foundation models that are pre-trained on large-scale multi-task datasets have also shown great potential in robotics. However, most existing robot foundation models rely solel...
In spite of the rapidly advancing global technological environment, the professional participation of women in technology, big data, analytics, artificial intelligence and information systems related domains remains proportionately low. Furthermore,...
Publish/subscribe (pub/sub) networks are a cornerstone of modern distributed systems, playing a crucial role in applications like the Internet of Things (IoT) and robotics. While runtime verification techniques seem ideal for ensuring the correctness...
Perlman) is the leader of the Maximals who transforms into an eastern lowland gorilla. In robot mode, he wields two Kukris which can fuse into a double-bladed