Problem

Problem{T}

Trajectory Optimization Problem. Contains the full definition of a trajectory optimization problem, including:

• dynamics model (RD.DiscreteDynamics)
• objective (Objective)
• constraints (ConstraintList)
• initial and final states
• Primal variables (state and control trajectories)
• Discretization information: knot points (N), time step (dt), and total time (tf)

Constructors:

Problem(model, obj, constraints, x0, xf, Z, N, tf)
Problem(model, obj, x0, tf; [xf, constraints, N, X0, U0, dt, integration])

where Z is a [RobotDynamics.SampledTrajectory].

Arguments

• model: A DiscreteDynamics model. If a ContinuousDynamics model is provided, it will be converted to a DiscretizedDynamics model via the integrator specified by the integration keyword argument.
• obj: Objective
• X0: Initial state trajectory. If omitted it will be initialized with NaNs, to be later overwritten by the solver.
• U0: Initial control trajectory. If omitted it will be initialized with zeros.
• x0: Initial state
• xf: Final state. Defaults to zeros.
• dt: Time step. Can be either a vector of length N-1 or a positive real number.
• tf: Final time. Set to zero.
• N: Number of knot points. Uses the length of the objective.
• integration: One of the defined integration types to discretize the continuous dynamics model.

Both X0 and U0 can be either a Matrix or a Vector{<:AbstractVector}.

cost(::Problem)

Compute the cost for the current trajectory

states(::Problem, args...)

Get the state trajectory.

controls(::Problem, args...)

Get the control trajectory

horizonlength(prob::Problem)

Number of knot points in the time horizon, i.e. the length of the sampled state and control trajectories.

Get the objective. Returns an AbstractObjective.

Get problem constraints. Returns ConstraintList.

get_model(prob::Problem)

Get the dynamics models used at each time step. Returns Vector{RobotDynamics.DiscreteDynamics}.

get_model(prob::Problem, k::Integer)

Get the dynamics model at time step k.

Get the trajectory. Returns an RobotDynamics.SampledTrajectory

get_initial_time(problem)

Get the initial time of the trajectory.

get_final_time(problem)

Get the final time of the trajectory.

Get the in initial state. Returns an AbstractVector.

Get the in initial state. Returns an AbstractVector.

Determines if the problem is constrained.

gettimes(Z)

Get a vector of times for the entire trajectory.

gettimes(::Problem)

Get the times for all the knot points in the problem.

initial_controls!(::Problem, U0::Vector{<:AbstractVector})
initial_controls!(::Problem, U0::AbstractMatrx)

Copy the control trajectory

initial_states!(::Problem, X0::Vector{<:AbstractVector})
initial_states!(::Problem, X0::AbstractMatrix)

Copy the state trajectory

initial_trajectory!(prob::Problem, Z)

Copies the trajectory data from Z to the problem.

set_initial_state!(prob::Problem, x0::AbstractVector)

Set the initial state in prob to x0

set_goal_state!(prob::Problem, xf::AbstractVector; objective=true, constraint=true)

Change the goal state. If the appropriate flags are true, it will also modify a GoalConstraint and the objective, assuming it's an LQRObjective.

rollout!(::Problem)

Simulate the dynamics forward from the initial condition x0 using the controls in the trajectory Z. If a problem is passed in, Z = prob.Z, model = prob.model, and x0 = prob.x0.