50 articles found
The WEEDINATOR autonomous agricultural robot project has reached a significant milestone after nearly a decade of development, demonstrating effective mechanical weed removal using a modified commercial Iseki tractor base. The system uses computer vision (OpenCV and YOLO26n on a Jetson Nano) combined with hydraulically-controlled cultivator claws for autonomous weeding in three axes.
Nathaniel Nifong has developed Stringman, an open-source ceiling-mounted robotic crane system that uses wire suspension to autonomously identify and pick up items scattered around a room. The system uses computer vision and a robotic gripper, with firmware based on LeRobot available on GitHub, and the creator is offering both build instructions and ready-made kits for interested users.
Carnegie Mellon University's Robotics Institute developed Erwin, an autonomous robot that detects fire blight disease in orchards using computer vision and robotic arms, winning the Amiga Innovation Award at the 2026 Farm Robotics Challenge. The system combines GPS, LIDAR, and AI-trained cameras to navigate orchard rows, identify infected trees, classify disease severity, and create spatial disease maps to assist farmers in targeted pruning during dormant seasons.
Deepak Pathak, an associate professor at Carnegie Mellon University's Robotics Institute, received the 2026 PAMI Young Researcher Award for his contributions to computer vision, machine learning, and robotics. Pathak's research focuses on enabling AI systems to learn from visual data and experiences with minimal human-labeled training, and he co-founded Skild AI, a robotics foundation model startup valued at over $14 billion.
Two recent funding announcements—one for battlefield surgical drones, another for autonomous anti-drone systems—reveal an uncomfortable truth: the same AI, computer vision, and robotics technologies are being deployed for both saving and taking lives. This convergence raises questions the robotics industry can no longer ignore.
Allen Control Systems (ACS) raised $200 million in Series B funding to scale production of Bullfrog, an autonomous counter-drone weapon station that uses AI, computer vision, and robotics to detect and neutralize unmanned aerial systems. The system is already deployed with the U.S. Army and Navy, and achieved a 100% success rate in recent military testing, with the funding supporting expanded manufacturing and new product development.
Robot Talk Episode 159 features an interview with Maria Koskinopoulou, an Assistant Professor in Robotics and Computer Vision at Heriot-Watt University, discussing her research on autonomous robotic manipulators for surgery, industry, and related applications. Her work spans robotic manipulation, perception, robot vision, medical robotics, and machine learning, supported by major UKRI and EU-funded projects.
Locus Robotics acquired Nexera Robotics to integrate its NeuraGrasp gripper technology into the Locus Array mobile manipulator, significantly expanding the robot's ability to handle diverse SKUs in warehouse environments. NeuraGrasp combines soft compliant membranes with computer vision and AI to dynamically grasp items ranging from porous polybags to irregularly shaped products, addressing a major bottleneck in robotic picking that suction cups alone cannot solve.
Automated Tire Inc. unveiled SmartBay, an AI-powered robotic platform that automates tire changes and vehicle inspections without removing wheels from vehicles. The system can reduce service times to 30 minutes while enabling one technician to manage three bays simultaneously, addressing labor shortages in automotive service by replacing manual, injury-prone work with computer vision and robotics.
Aniket Roy, a PhD graduate from Johns Hopkins University, discusses his research on resource-constrained image generation and visual understanding, focusing on making advanced generative AI and computer vision systems more efficient and practical. His work spans diffusion models, few-shot learning, personalized image generation, and multimodal learning, with techniques like FeLMi, Cap2Aug, DiffNat, and DuoLoRA designed to enable models to operate effectively with limited data and computational resources.
GroundedPlanBench is a research benchmark for spatially grounded long-horizon task planning in robot manipulation, enabling robots to understand and execute complex multi-step tasks in physical environments. The work combines computer vision and AI planning to improve robots' ability to interpret spatial relationships and execute manipulation tasks.
A maker built a robot air hockey opponent featuring a custom-drilled air hockey table and a dual-motor gantry system controlled by computer vision. The robot uses an overhead camera with Python/OpenCV to track the puck position and Arduino code to actuate the paddle, demonstrating practical applications of robotics control and real-time image processing for game-playing automation.
A US Defense official disclosed that the military may use generative AI chatbots to rank target lists and make strike recommendations, which would then be reviewed by human operators. The Pentagon is fielding these systems for classified settings alongside its existing Maven computer vision platform, representing a shift toward using large language models like ChatGPT, Claude, and Grok to accelerate targeting decisions, though the systems remain less battle-tested than traditional military AI.
A hobbyist engineer built a mobile robotic platform controlled by a fish's swimming movements, using computer vision to track the fish's position and translate it into tank movement commands. The project demonstrates creative application of robotics and computer vision technology to an unconventional pet ownership concept.
Researchers at the University of Limerick developed a drone-based system combining aerial surveillance with machine learning algorithms to detect and map plastic litter on beaches. The technology uses computer vision to identify plastic as small as 1cm from 30 meters altitude, paired with a free mobile app that provides volunteers with GPS coordinates for targeted cleanup efforts.
You might not have heard of the Nex Playground, but it's a tiny gaming system built entirely around Kinect-like games. With its camera and computer vision processing, the $249 Nex Playground can track...
A maker demonstrates an analog-based light-following robot using only simple components like light-dependent resistors (LDRs), op-amps, and 555 timer ICs, without requiring a microcontroller or computer vision system. The design evolves from simple binary steering to PWM-based motor control for smoother navigation, showcasing how classic analog electronics principles can solve robotics problems without digital processing.
Snap is spinning off its augmented reality glasses business into a separate subsidiary called Specs Inc. to attract external investors and partnerships while competing with Meta's AR initiatives. The new entity will launch next-generation standalone AR glasses this year with improved form factor, lighter design, and AI-powered capabilities that use computer vision and behavioral understanding to assist users.
Researchers have developed UniRG, a system that scales medical imaging report generation using multimodal reinforcement learning to improve the accuracy and efficiency of automated diagnostic reporting. The work demonstrates advances in applying reinforcement learning and multimodal AI to the healthcare domain, combining computer vision and natural language processing for clinical applications.
Bucket Robotics, a YC-backed startup founded by former autonomous vehicle engineer Matt Puchalski, made its debut at CES 2026 with an AI-powered vision inspection system for manufacturing quality control. The company uses advanced computer vision and synthetic data generation from CAD files to automate surface defect detection on industrial parts like car door handles, addressing a gap in manufacturing automation that currently relies on manual inspection.
This podcast episode features Professor Roberto Martín-Martín from the University of Texas at Austin discussing his research in embodied AI, robotics, computer vision, and machine learning for autonomous agents. The conversation explores how robots can perceive, learn, and act in the real world, covering topics from manipulation tasks to mobile robotics and human-robot interaction.
This podcast episode covers major AI and robotics developments from late November 2025, including new model releases (Google's Gemini 3, Anthropic's Opus 4.5, OpenAI's GPT-5.1) and robotics innovations like Sunday Robotics' Memo humanoid robot and a $5.6B funding round for Physical Intelligence. The episode also discusses AI safety, policy updates including European GDPR/AI Act changes, Meta's SAM 3 computer vision model, and research advances in self-supervised learning and embodied AI.
Point One Navigation, a San Francisco-based startup, raised $35 million in Series C funding led by Khosla Ventures, bringing its valuation to $230 million. The company has developed precise location technology using augmented GNSS, computer vision, and sensor fusion that achieves centimeter-level accuracy for autonomous vehicles, robotics, drones, and agricultural equipment, with over 150,000 vehicles already deployed and tenfold growth in manufacturer adoption over the past year.
Initiative will fund over 100 doctoral students researching machine learning, computer vision, and natural-language processing at nine universities.
In his keynote address at CVPR, Swami Sivasubramanian considers the many ways that Amazon incorporates computer vision technology into its products and makes it directly available to AWS customers.
A research group at Carnegie Mellon University's Robotics Institute will soon host the CMU Vision-Language-Autonomy Challenge, bringing researchers together at the intersection of computer vision, nat...
A combination of generative AI and computer vision imaging tunnels is helping Amazon proactively improve the customer experience.
How an AWS customer uses Lookout for Vision to build custom computer vision models to automate quality inspection and detect defects.
The International Conference on Computer Vision (ICCV 2021) will be hosted virtually next week. We're excited to share all the work from SAIL that will be presented, and you'll find links to papers,...
University of Wisconsin-Madison associate professor and ARA recipient has authored a series of pioneering papers on real-time object instance segmentation.
Topics range from specific applications, such as computer vision, to more general problems, such as continual learning, to popular AI methods, such as variational autoencoders.
Research topics range from visual anomaly detection to road network extraction, regression-constrained neural-architecture search to self-supervised learning for video representations.
Company is testing a new class of robots that use artificial intelligence and computer vision to move freely throughout facilities.
Amazon’s director of applied science in Adelaide, Australia, believes the economic value of computer vision has “gone through the roof".
Senior principal scientist Aleix M. Martinez on why computer vision research has only begun to scratch the surface.
How a math-loving student travelled 7,000 miles to pursue a passion and wound up becoming an applied scientist.
Graduate Research Fellows Program, launched in 2021, supports research in automated reasoning, computer vision, robotics, language technology, machine learning, operations research, and data science.
Method uses metric learning to determine whether images depict the same product.
Amazon’s Joe Tighe on the major trends he sees in the field of computer vision.
A combination of deep learning, natural language processing, and computer vision enables Amazon to hone in on the right amount of packaging for each product.
Natarajan discusses his work in the field of computer vision, machine learning, and multimedia processing.
In a one-hour virtual presentation, Medioni describes his personal, 40-year career journey through academia, startups, and Amazon.
Efficient learning and the capacity for abstraction are attributes that will probably require new insights — but self-supervised learning could help.
Amazon Graduate Research Fellows Program supports research in automated reasoning, computer vision, robotics, language technology, machine learning, operations research, and data science.
Polito is one of the featured speakers at the first virtual Amazon Web Services Machine Learning Summit on June 2.
Amazon Machine Learning Research Award recipient utilizes a combination of people and machine learning models to illuminate the planet's incredible biodiversity.
Amazon distinguished scientist Gérard Medioni on the complexities of “understanding your environment through visual input”.
Amaia Salvador helped organize this week's Women in Computer Vision workshop held in conjunction with ECCV 20.
Amazon Scholar Thomas Brox sees promise in unsupervised learning, generative models, and integrating machine learning and geometry.
20tree.ai is on a mission to help protect the Earth’s forests by providing data-driven and actionable planet intelligence.
