Abstract
Planning plays a role in achieving long-term behaviour (persistent
autonomy) without human intervention. Such behaviour
engenders plans which are expected to last over many
hours, or even days. Such a problem is too large for current
planners to solve as a single planning problem, but is
well-suited to decomposition and abstraction planning techniques.
We present a novel approach to bottom-up decomposition
into a two-layer hierarchical structure, which dynamically
constructs planning problems at the abstract layer of the
hierarchy using solution plans from the lower layer.
We evaluate this approach in the context of persistent autonomy
in autonomous underwater vehicles, showing that
compared to strictly top-down approaches the bottom-up approach
leads to more robust solution plans of higher quality
autonomy) without human intervention. Such behaviour
engenders plans which are expected to last over many
hours, or even days. Such a problem is too large for current
planners to solve as a single planning problem, but is
well-suited to decomposition and abstraction planning techniques.
We present a novel approach to bottom-up decomposition
into a two-layer hierarchical structure, which dynamically
constructs planning problems at the abstract layer of the
hierarchy using solution plans from the lower layer.
We evaluate this approach in the context of persistent autonomy
in autonomous underwater vehicles, showing that
compared to strictly top-down approaches the bottom-up approach
leads to more robust solution plans of higher quality
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 4th ICAPS Workshop on Planning and Robotics (PlanRob 2016) |
| Number of pages | 8 |
| Publication status | Published - 2016 |