Autonomous Vehicles Navigating Urban Environments using Spatial Intelligence
Let’s take an example of autonomous vehicle that is driving on a busy city road (environment) that includes tasks like navigating intersections, avoiding pedestrians, and following traffic laws.
In this scenario, spatial intelligence is applied, the components of spatial intelligence are utilized the following manner:
- Perception: The vehicle is equipped with multiple sensor and cameras that create real time, high resolution 3D map and the vehicle identifies the other vehicles, pedestrians, traffic signs and road marking using computer vision.
- Reasoning: The gathered information is utilized to calculate the safest path to the destination. This involves dynamic planning algorithms that adjusts the route based on information like traffic congestion and road closures. The AI also calculates risks and identify how to safely navigate these risks.
- Execution: The vehicle controls the speed, steering and brakes according to the reasoning component and the vehicle follows traffic rules which requires understanding of spatial relationships and applicable rules.
Spatial intelligence in AI
Spatial Intelligence is the capacity to manipulate, perceive, and reason about spatial dimensions and relationships. In AI, spatial intelligence refers to the capability of algorithms and systems to process and understand the physical space around them. In this article, we are going to explore more about Spatial Intelligence and AI.
Table of Content
- What is Spatial Intelligence in Human Cognition?
- Key Components of Spatial Intelligence in AI
- 1. Perception
- 2. Reasoning
- 3. Execution
- Autonomous Vehicles Navigating Urban Environments using Spatial Intelligence
- Application of Spatial Intelligence in AI
- Conclusion