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Built on CRW/RW controllers, it would at site quality, site fidelity,
etc. aspects of foraging theory.
This would fit well with energy efficient/aware algorithms, because it would
track optimal performance in terms of energy (objects) brought to the
nest/discovered per unit of energy used (battery).
Blocked by #652 (other perception models). This could also incorporate aspects
of other papers where robots wait in the nest until some threshold is reached
before deciding to go out and expend energy.
As part of this, I should investigate how using foraging yield as a performance
measure compares against block collection rate (i.e., the most highly performing
swarm may not be the most energy efficient).
From Talamali2020.
The text was updated successfully, but these errors were encountered:
Built on CRW/RW controllers, it would at site quality, site fidelity,
etc. aspects of foraging theory.
This would fit well with energy efficient/aware algorithms, because it would
track optimal performance in terms of energy (objects) brought to the
nest/discovered per unit of energy used (battery).
Blocked by #652 (other perception models). This could also incorporate aspects
of other papers where robots wait in the nest until some threshold is reached
before deciding to go out and expend energy.
As part of this, I should investigate how using foraging yield as a performance
measure compares against block collection rate (i.e., the most highly performing
swarm may not be the most energy efficient).
From Talamali2020.
The text was updated successfully, but these errors were encountered: