What is Coordinated Exploration?
In the context of robotics, coordinated exploration refers to the deployment of multi-robot systems in order to explore an environment. These multi-robot systems collectively develop a structural model of that environment by moving through and navigating around it.
Inside Hardware: Thermal System Design
The Shield AI team designs sophisticated thermal systems for our aerial robot, Nova. Lead Hardware Designer, Christian Wester, provides insight into what challenges our engineers must overcome in creating effective designs.
How Do Robots Learn Through Exploration?
A robotic system will acquire more experience the more it operates. This experience translates into learned information about how the actions the robot takes will impact its ability to interact with its environment.
Inside Hardware: Designing a Circuit Board
Circuit boards are the glue that integrates all of a product’s higher-level system features together. At Shield AI, circuit board design for our robot is particularly interesting given our size and weight constraints.
How do Robots Communicate with Each Other?
In terms of multi-robot systems, the ability to communicate enables the robots to make coordinated decisions of who should go where and when, and to assess the reason why a particular robot is better suited for the task.
Our Philosophy on Professional Development
At Shield AI, we have established a talent development model focused on the professional growth of our employees. Shield AI’s Head of Talent elaborates on how we seek to provide our team with the resources and training they need to become their best.
What is Multi-Robot Exploration?
For a robotic system, exploration involves the system making decisions of where it should go in order to acquire information and learn about its environment. Multi-robot exploration applies to systems in which multiple robots are working together.
How Artificial Intelligence Manifests Through Exploration
As a robot explores, intelligence starts to manifest through the system’s ongoing assessment of its observations. Specifically, the robot will assess each observation’s informative value and information gain associated with it.