Robotics design company, Boston Dynamics, has released the latest update for its quadruped robot – Spot. The new update named “Spot Release 3.0” gives it better capabilities to inspect and improve data collection.
Spot’s automated inspections have now been streamlined for effective data capture and processing. Multiple tasks can be scheduled for Spot, such as collecting photos, thermal images, point clouds, and other critical data; processing that data into valuable signals at the edge with computer vision models; and create custom uploads to send those signals to existing systems, which makes it easy to keep all data in one place for analysis and review.
The new update also improves Autowalk, and Spot also has been given better planning capabilities to find the best path to perform target actions. Its pathfinding capacity has been improved to adapt to changes in its inspection paths, such as new obstacles.
Another big feature of the new update is improved compatibility to cloud services from Microsoft, Amazon, and IBM. Spot’s sensing capabilities can be an alternative to manual data logging or IoT instrumentation and installation of smart sensors on old infrastructure. This feature makes it possible to automatically integrate data collected during Spot’s Autowalk into a broader data-based workflow of companies. The data can be combined with other sources of information and processed with analytics and machine learning tools for tasks such as tracking trends, detecting anomalies, and triggering warnings.
Release 3.0 makes data capture more reliable and easier to process. Computer vision models can now be connected to Spot, adding valuable context to teleoperation and turning raw mission data into actionable signals at the edge.
Other new features include remotely restart payloads, easily configuring payload parameters, Arm improvements such as added functionality for push-bar doors, revamped grasping UX, and updated SDK.
Subscribe to our NewsletterGet the latest updates and relevant offers by sharing your email.
Victor is an aspiring Data Scientist & is a Master of Science in Data Science & Big Data Analytics. He is a Researcher, a Data Science Influencer and also an Ex-University Football Player. A keen learner of new developments in Data Science and Artificial Intelligence, he is committed to growing the Data Science community.