
How compact cobot integration enhances autonomous mobile robot applications
Kassow said its cobots can reach difficult-to-access areas, handle heavier objects, and perform demanding tasks with accuracy. | Source: Kassow Robots The increasing automation of warehouse pick-and-place, palletizing, and machine-tending tasks has introduced new technologies. Robotics and automation have drastically changed operations as productivity needs and labor shortages impact the industry. Workers are interacting with autonomous mobile robots and collaborative robots, or cobots, integrat
Compact collaborative robots, or cobots, are being integrated onto autonomous mobile robots to automate warehouse tasks like picking, palletizing, and machine tending. Seven-axis cobot arms mounted on mobile robots offer greater range of motion and can access harder-to-reach areas compared to traditional six-axis arms, while controllers built into the arm itself eliminate the need for separate control cabinets. This integration reduces labor needs for repetitive tasks, allows workers to focus on more complex work, and improves job satisfaction by reducing physical strain. Unlike older automated systems, these mobile manipulators use built-in sensors for navigation rather than requiring physical infrastructure guides, making them more flexible and cost-effective solutions as warehouses face ongoing labor shortages.
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Browse AI courses on MavenGoogle DeepMind releases new advanced robotics AI model and next-generation gene prediction model
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Can AI agents program industrial robots without training data? Berkeley says yes
The new RoboSimStudio is an open-source project that enables agentic AI coding of robotic simulation environments. | Credit: UC Berkeley UC Berkeley and NVIDIA have released open-source tools for a new approach: enabling teams of AI coding agents to write, simulate, and refine readable robot programs. Since the early days of industrial robots, programming, tuning, and troubleshooting robotic workcells has taken weeks to months. New research coming out of UC Berkeley has demonstrated that new age

Boston Dynamics adds wheels to Atlas humanoid to test whole-body control
Bridging the divide between deterministic physics-based control and policy-driven adaptation, Boston Dynamics has deployed a hybrid locomotion architecture on a wheeled variant of its Atlas humanoid. The “experiment” combined classical model-based motor control with whole-body reinforcement learning to maintain dynamic stability across unstructured, real-world terrain. In the video, Andy Wu, controls engineer for Atlas at Boston Dynamics, highlights some recent experiments that he

Practice Makes Precise: At CoRL, NVIDIA and Partners Reveal How Robots Rehearse Delicate Work in Simulation
Simulation, which has long been the proving ground for robots learning to walk, roll and hop, is now helping researchers teach robots tasks that require a finer touch: aligning gears, connecting cables and assembling small components. The shift from locomotion to manipulation is taking center stage at this week’s Conference on Robot Learning (CoRL) in Austin, Texas, alongside the rise of agentic robotics — a new paradigm that integrates frontier agents to create interpretable code for physical

Memories.ai builds standardized egocentric video pipeline
Memories.ai models label every clip: Memories-H0 for hand pose, EgoAction for action segments. | Credit: Memories.ai Memories.ai is building a data pipeline for robotics companies that combines standardized video collection with AI-powered annotation to turn everyday egocentric footage into training data for robots. The San Francisco-based company is developing software and AI to help robots understand the physical world. It builds video-understanding models and data infrastructure, and it colle