Systems and methods for intelligently calibrating infrastructure devices using onboard sensors of an autonomous agent
A system for intelligently implementing an autonomous agent that includes an autonomous agent, a plurality of infrastructure devices, and a communication interface. A method for intelligently calibrating infrastructure (sensing) devices using onboard sensors of an autonomous agent includes identifying a state of calibration of an infrastructure device, collecting observation data from one or more data sources, identifying or selecting mutually optimal observation data, specifically localizing a subject autonomous agent based on granular mutually optimal observation data, identifying dissonance in observation data from a perspective of a subject infrastructure device, and recalibrating a subject infrastructure device.
1. A method for determining a calibration error associated with at least one of an infrastructure device of a set of infrastructure devices and an autonomous agent, the method comprising:
receiving, at a computing system:
a first stream of observation data from the infrastructure device;
a second stream of observation data from an autonomous agent; and
health status data from the infrastructure device, wherein the health status data comprises at least one of diagnostic information and resource utilization information associated with the infrastructure device;
determining an association between the first stream of observation data and the second stream of observation data;
determining a dissonance between the first and second streams of observation data based on the association;
determining a calibration error based on the dissonance and the health status data; and
updating a state of calibration of at least one of the infrastructure device and the autonomous agent based on the calibration error.
2. The method of claim 1 , wherein the first stream of observation data is received from a set of sensors onboard the infrastructure device.
3. The method of claim 2 , wherein the set of sensors comprises a camera, wherein a focal length of the camera is selected based at least in part on a distance to a second infrastructure device of the set of infrastructure devices.
4. The method of claim 2 , wherein the first stream of observation data is associated with a first set of timestamps, and wherein the association is determined at least in part based on the first set of timestamps.
5. The method of claim 1 , wherein the set of infrastructure devices defines a field of sensing, and wherein the autonomous agent is arranged within the field of sensing.
6. The method of claim 1 , wherein determining the association comprises determining a set of mutually optimal observation data based on the first stream of observation data and the second stream of observation data.
7. The method of claim 6 , further comprising localizing the autonomous agent based on the mutually optimal observation data.
8. The method of claim 1 , wherein the computing system is a remote computing system.
9. A system for determining a calibration error associated with at least one of an infrastructure device of a set of infrastructure devices and an autonomous agent, the system comprising:
the set of infrastructure devices, wherein the infrastructure device comprises an onboard sensor system; and
a computing system in communication with the set of infrastructure devices and the autonomous agent, wherein the computing system is configured to:
receive a first stream of observation data from the onboard sensor system of the infrastructure device;
receive a second stream of observation data from the autonomous agent;
receive a third stream of data from the infrastructure device, wherein the third stream of data comprises at least one of diagnostic information and resource utilization information associated with the infrastructure device;
determine an association between the first stream of observation data and the second stream of observation data;
determine a dissonance between the first and second streams of observation data based on the association;
determine a calibration error based on the dissonance and the third stream of data; and
update a state of calibration of at least one of the infrastructure device and the autonomous agent based on the calibration error.
10. The system of claim 9 , wherein the computing system is a remote computing system.
11. The system of claim 9 , wherein the onboard sensor system comprises a camera associated with a selected focal length.
12. The system of claim 11 , wherein the selected focal length is determined based at least in part on a distance between the infrastructure device and a second infrastructure device of the set of infrastructure devices.
13. The system of claim 12 , wherein the selected focal length is a fixed focal length.
14. The system of claim 9 , wherein:
the first stream of observation data is associated with a first set of timestamps;
the second stream of observation data is associated with a second set of timestamps; and
the association is determined at least in part based on an overlap between the first set of timestamps and the second set of timestamps.
15. The system of claim 14 , wherein the association comprises a set of mutually optimal observation data determined based on the overlap.
16. The system of claim 15 , wherein a location of the autonomous agent is determined at the computing system based on the mutually optimal observation data.