Les 10 concurrents forcen.tech les plus visités

bostondynamics.com

Boston Dynamics is in search of team members who revel in robotics. Find an open role and start your career with us today.

novarctech.com

Harder Mechanical is a nationally recognized contractor with an outstanding reputation. They were looking at welding automation options and discovered Novarc Technologies.

sereact.ai

Automated returns handling with dual-arm robotic stations powered by Cortex. Inspect, classify, and sort returned items in live warehouse production.

mujin-corp.com

Mujin builds intelligent robotics software for factories and warehouses. MujinOS enables no-code deployment of palletizing, picking, and fleet automation.

therobotreport.com

The Robot Report provides robotics news, research, analysis and investment tracking for engineers, technology, and business professionals.

automationmag.com

Alicia Butty is a welder working at Butty Manufacturing, her family’s custom fabrication business near Brantford, Ontario. The company engineers and builds

dobot.cn

越疆机器人专注于协作机器人的研发与应用，是全球先进的智能机器人研发制造商。拥有cr、crs、mg400、m1pro、nova、magician 六大系列十余款协作机器人，覆盖 3c、汽车、半导体、化工、医疗、金属加工、食品饮料、新零售、教育等多个行业。服务热线：400-800-7266。

umi-gripper.github.io

We present Universal Manipulation Interface (UMI) -- a data collection and policy learning framework that allows direct skill transfer from in-the-wild human demonstrations to deployable robot policies. UMI employs hand-held grippers coupled with careful interface design to enable portable, low-cost, and information-rich data collection for challenging bimanual and dynamic manipulation demonstrations. To facilitate deployable policy learning, UMI incorporates a carefully designed policy interface with inference-time latency matching and a relative-trajectory action representation. The resulting learned policies are hardware-agnostic and deployable across multiple robot platforms. Equipped with these features, UMI framework unlocks new robot manipulation capabilities, allowing zero-shot generalizable dynamic, bimanual, precise, and long-horizon behaviors, by only changing the training data for each task. We demonstrate UMI’s versatility and efficacy with comprehensive real-world experiments, where policies learned via UMI zero-shot generalize to novel environments and objects when trained on diverse human demonstrations.

odriverobotics.com

ODrive - High performance motor control for robotics.

synthiam.com

Better Navigator Hector SLAM-based NMS navigation that maps with LiDAR/depth, saves waypoints, plans paths and avoids obstacles for autonomous travel