You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Copy file name to clipboardExpand all lines: doc/trajopt_planner/trajopt_planner_tutorial.rst
+8-4Lines changed: 8 additions & 4 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -56,10 +56,14 @@ How TrajOpt works
56
56
Motion planning problem in TrajOpt is defined by a set of cost (COST) and constraints (CNT) functions that are added to ``TrajOptProblem`` through ``ConstructProblem`` function. This function gets the information regarding to the problem (``ProblemInfo``) which carries different types of information explained below:
57
57
58
58
- **BasicInfo**: This type holds general information of the optimization algorithm. (These parameters are further investigated in the following section):
59
-
* `n_steps`: The number of steps from start to goal
60
-
* `convex_solver`: Which convex solver is to be used
61
-
* `use_time`: Set to `false` value to use a unitless timestep. x1-x0 is the velocity
62
-
* `start_fixed`: Set to `true` to add a constraint for the current joint value
59
+
60
+
- *n_steps*: The number of steps from start to goal
61
+
62
+
- *convex_solver*: Which convex solver is to be used
63
+
64
+
- *use_time*: Set to `false` value to use a unitless timestep. x1-x0 is the velocity
65
+
66
+
- *start_fixed*: Set to `true` to add a constraint for the current joint value
63
67
64
68
- **InitInfo**: It defines how to initialize the optimization problem by setting a guessed trajectory in a matrix whose number of rows is the same as number of timesteps and whose number of columns is equal to the degrees of freedom. There are three different types for initialization:
0 commit comments