NASA's Perseverance Rover Embarks on AI-Driven Drive on Mars, Captivating Visuals of Autonomous Decision-Making.
A recent animation created by NASA using the Caspian visualization tool has shed light on the autonomous decision-making process of the Perseverance rover during a 807-foot drive on the rim of Jezero Crater. The animation is an attempt to understand how the rover's AI system, also known as "drivers," navigates its path using data acquired from high-resolution orbital imagery and terrain-slope data.
The first step in this process involved analyzing the HiRISE camera data aboard NASA's Mars Reconnaissance Orbiter to identify critical features such as bedrock, outcrops, hazardous boulder fields, sand ripples, and more. This information was then used by generative artificial intelligence to generate a continuous path with waypoints - fixed locations where the rover takes on new instructions.
The animation shows two paths: the actual track taken by the rover's wheels (depicted in pale blue) and several alternative options considered by the AI system at any given moment, represented by black lines snaking out in front of the rover. The white terrain map in the background was generated using data collected during the drive.
A critical feature of this animation is the inclusion of a pale blue circle near the end of the animation, which represents a waypoint - a point where the AI system has instructed the rover to take on new instructions. This addition provides insight into how the AI system plans its path and makes adjustments as needed.
This effort aims to provide valuable insights into how autonomous systems can operate effectively in complex environments like Mars.
A recent animation created by NASA using the Caspian visualization tool has shed light on the autonomous decision-making process of the Perseverance rover during a 807-foot drive on the rim of Jezero Crater. The animation is an attempt to understand how the rover's AI system, also known as "drivers," navigates its path using data acquired from high-resolution orbital imagery and terrain-slope data.
The first step in this process involved analyzing the HiRISE camera data aboard NASA's Mars Reconnaissance Orbiter to identify critical features such as bedrock, outcrops, hazardous boulder fields, sand ripples, and more. This information was then used by generative artificial intelligence to generate a continuous path with waypoints - fixed locations where the rover takes on new instructions.
The animation shows two paths: the actual track taken by the rover's wheels (depicted in pale blue) and several alternative options considered by the AI system at any given moment, represented by black lines snaking out in front of the rover. The white terrain map in the background was generated using data collected during the drive.
A critical feature of this animation is the inclusion of a pale blue circle near the end of the animation, which represents a waypoint - a point where the AI system has instructed the rover to take on new instructions. This addition provides insight into how the AI system plans its path and makes adjustments as needed.
This effort aims to provide valuable insights into how autonomous systems can operate effectively in complex environments like Mars.