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Python bindings for methods of GcsTrajectoryOptimization::Subgraph for adding generic costs and constraints. #22156

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Nov 14, 2024
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Python bindings for methods of GcsTrajectoryOptimization::Subgraph for adding generic costs and constraints. #22156

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46 changes: 45 additions & 1 deletion bindings/pydrake/planning/planning_py_trajectory_optimization.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -346,6 +346,15 @@ void DefinePlanningTrajectoryOptimization(py::module m) {
constexpr auto& cls_doc = doc.GcsTrajectoryOptimization;
py::class_<Class> gcs_traj_opt(m, "GcsTrajectoryOptimization", cls_doc.doc);

const std::unordered_set<
geometry::optimization::GraphOfConvexSets::Transcription>
all_transcriptions = {
geometry::optimization::GraphOfConvexSets::Transcription::kMIP,
geometry::optimization::GraphOfConvexSets::Transcription::
kRelaxation,
geometry::optimization::GraphOfConvexSets::Transcription::
kRestriction};

// Subgraph
const auto& subgraph_doc = doc.GcsTrajectoryOptimization.Subgraph;
py::class_<Class::Subgraph>(gcs_traj_opt, "Subgraph", subgraph_doc.doc)
Expand Down Expand Up @@ -409,7 +418,42 @@ void DefinePlanningTrajectoryOptimization(py::module m) {
.def("AddContinuityConstraints",
&Class::Subgraph::AddContinuityConstraints,
py::arg("continuity_order"),
subgraph_doc.AddContinuityConstraints.doc);
subgraph_doc.AddContinuityConstraints.doc)
.def("vertex_duration", &Class::Subgraph::vertex_duration,
subgraph_doc.vertex_duration.doc)
.def("edge_constituent_vertex_durations",
&Class::Subgraph::edge_constituent_vertex_durations,
subgraph_doc.edge_constituent_vertex_durations.doc)
// As in trajectory_optimization_py.cc, we use a lambda to *copy*
// the decision variables; otherwise we get dtype=object arrays
// cannot be referenced.
.def(
"vertex_control_points",
[](const GcsTrajectoryOptimization::Subgraph& self)
-> MatrixX<symbolic::Variable> {
return self.vertex_control_points();
},
subgraph_doc.vertex_control_points.doc)
.def(
"edge_constituent_vertex_control_points",
[](const GcsTrajectoryOptimization::Subgraph& self)
-> std::pair<MatrixX<symbolic::Variable>,
MatrixX<symbolic::Variable>> {
return self.edge_constituent_vertex_control_points();
},
subgraph_doc.edge_constituent_vertex_control_points.doc)
.def("AddVertexCost", &Class::Subgraph::AddVertexCost, py::arg("e"),
py::arg("use_in_transcription") = all_transcriptions,
subgraph_doc.AddVertexCost.doc)
.def("AddVertexConstraint", &Class::Subgraph::AddVertexConstraint,
py::arg("e"), py::arg("use_in_transcription") = all_transcriptions,
subgraph_doc.AddVertexConstraint.doc)
.def("AddEdgeCost", &Class::Subgraph::AddEdgeCost, py::arg("e"),
py::arg("use_in_transcription") = all_transcriptions,
subgraph_doc.AddEdgeCost.doc)
.def("AddEdgeConstraint", &Class::Subgraph::AddEdgeConstraint,
py::arg("e"), py::arg("use_in_transcription") = all_transcriptions,
subgraph_doc.AddEdgeConstraint.doc);

// EdgesBetweenSubgraphs
const auto& subgraph_edges_doc =
Expand Down
49 changes: 49 additions & 0 deletions bindings/pydrake/planning/test/trajectory_optimization_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -331,6 +331,55 @@ def test_gcs_trajectory_optimization_basic(self):
np.testing.assert_allclose(restricted_traj_start, start, atol=1e-6)
np.testing.assert_allclose(restricted_traj_end, end, atol=1e-6)

# We can add additional costs and constraints with the placeholder
# variables.
vertex_duration = regions.vertex_duration()
vertex_control_points = regions.vertex_control_points()
edge_constituent_vertex_durations = (
regions.edge_constituent_vertex_durations()
)
edge_constituent_vertex_control_points = (
regions.edge_constituent_vertex_control_points()
)

vertex_cost = sum([
vertex_duration,
vertex_control_points[0, 0],
vertex_control_points[0, 1],
])
edge_cost = sum([
edge_constituent_vertex_durations[0],
edge_constituent_vertex_durations[1],
edge_constituent_vertex_control_points[0][0, 0],
edge_constituent_vertex_control_points[0][0, 1],
edge_constituent_vertex_control_points[1][0, 0],
edge_constituent_vertex_control_points[1][0, 1]
])
vertex_constraint = vertex_cost >= 0
edge_constraint = edge_cost >= 0

regions.AddVertexCost(e=vertex_cost)
regions.AddVertexConstraint(e=vertex_constraint)
regions.AddEdgeCost(e=edge_cost)
regions.AddEdgeConstraint(e=edge_constraint)

all_transcriptions = {
GraphOfConvexSets.Transcription.kMIP,
GraphOfConvexSets.Transcription.kRelaxation,
GraphOfConvexSets.Transcription.kRestriction
}
regions.AddVertexCost(e=vertex_cost,
use_in_transcription=all_transcriptions)
regions.AddVertexConstraint(e=vertex_constraint,
use_in_transcription=all_transcriptions)
regions.AddEdgeCost(e=edge_cost,
use_in_transcription=all_transcriptions)
regions.AddEdgeConstraint(e=edge_constraint,
use_in_transcription=all_transcriptions)

traj, result = gcs.SolvePath(source, target)
self.assertTrue(result.is_success())

# Test that removing all subgraphs, removes all vertices and edges.
self.assertEqual(len(gcs.graph_of_convex_sets().Vertices()),
len(source.Vertices())
Expand Down