Blog

Unlock the Data that Matters Most

As a quadruped robot, Spot can operate virtually anywhere a person can—going up and down stairs, indoors or outdoors, and through cramped or confined spaces. While this mobility can be impressive on its own, its real value is in automating sensing and inspection in areas inaccessible with wheeled or tracked robots and drones. You can send Spot into areas designed for people, that are unstructured, or even hazardous, to collect the data you need to understand what's going on in your facility or at your jobsite.

Break Through Supply Chain Blocks with Automated Container Unloading

Customers finding bare spots on grocery store shelves or waiting months instead of weeks for a furniture delivery are feeling the ripple effects of supply chain disruptions—with more shortages and delays anticipated as the holiday season approaches.

Much of the merchandise is out there, stalled in cargo ports loaded with shipping containers at unprecedented volumes. Labor shortages have slowed the pace of unloading containers and warehouses to a crawl, and ports on both U.S. coasts have required ships to idle at sea for days until space opens up in the yards. Those delays are straining the supply of cargo containers at a time when demand for goods is hardly slowing down—rather, U.S. imports are projected to rise through the end of the year.  

What is Dynamic Sensing?

Artificial intelligence is changing the way businesses operate. AI systems demand a continuous flow of repeatable data that’s difficult to collect on physical sites. Today, the health of equipment in facilities is monitored through a mix of fixed sensors and operator rounds. These sensors are limited in perspective, expensive to scale, and can’t adapt to changes. Companies make up the data deficit by spending human resources on tedious data collection. But people are too inconsistent at data collection and too valuable to be feeding an AI system all day. Instead, they should be at the top of the value chain turning data-driven insights into action.

3 Benefits of Continuous Data

Artificial Intelligence (AI) is rapidly becoming a routine aspect of business operations. A recent survey from Deloitte found 34% of respondents had already begun implementing AI systems to support intelligent automation, while 52% plan to implement these systems in the next three years. But implementing and operationalizing AI is often easier said than done, especially without continuous, reliable data about your operations.

Asset Management for the Rest of Us

There is a disconnect in manufacturing.

On one hand, artificial intelligence (AI) and machine learning (ML) have made huge advancements and offer tremendous potential to save maintenance costs and increase uptime by identifying problems before they escalate. On the other hand, the relevant data these ML models need is often hard to gather and aggregate into disparate systems. Legacy assets plod along without realizing the full promise of digital transformation and Industry 4.0.

But what if there were an easy way to access the right data—in the right place at the right time? 

Spot Release 3.0: Flexible autonomy and repeatable data capture

Artificial intelligence is changing how businesses operate, furthering applications from enterprise asset management to construction site tracking and everything in between. AI systems depend on data, but reliable, repeatable data is hard to collect in busy, remote, or hazardous work sites. Spot solves this problem by acting as a dynamic sensor, collecting data where and when it’s needed, freeing operators from tedious data collection and enabling companies to accelerate their digital transformations.

How to Gather Better Data and Reduce Dosage in Nuclear Facilities

Nuclear power constitutes more than half of the non-carbon electricity generated in the United States, according to the US Energy Information Administration. Given global decarbonization efforts, there is a strong likelihood that nuclear power will become a more significant contender in energy production as time progresses and demand continues to climb. 

Build It. Break It. Fix It.

Atlas jogs up to the embanked yellow plywood panels, bouncing with ease from one to the next until the humanoid robot has made its way up to a box that sits at about waist level. Sensing the gap in front of it, Atlas pauses, plants its feet, and broad jumps across to a table on the other side. 

It sticks the landing. By all appearances, Atlas is cruising. But then, as the robot descends the three stairs back to the floor, a geyser of pink hydraulic fluid erupts from its left knee. The robot gets a few more staggered steps in as the oil gushes into the air, and then collapses in a heap. 

Flipping the Script with Atlas

What does it take for a robot to run, flip, vault, and leap like an athlete? Creating these high-energy demonstrations is a fun challenge, but our technical goals go beyond just creating a flashy performance. On the Atlas project, we use parkour as an experimental theme to study problems related to rapid behavior creation, dynamic locomotion, and connections between perception and control that allow the robot to adapt – quite literally – on the fly. 

Atlas | Leaps, Bounds, and Backflips

For the first time today, both Atlas robots have completed the complex obstacle course flawlessly. Or, almost flawlessly.

The first of the two robots ran up a series of banked plywood panels, broad jumped a gap, and ran up and down stairs in the course set up on the second floor of the Boston Dynamics headquarters. The second robot leapt onto a balance beam and followed the same steps in reverse, and then the first robot vaulted over the beam. Both landed two perfectly synchronized backflips, and the video team has captured every move.