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A Julia package for solving constrained trajectory optimization problems:

minimize        cost_T(state_T; parameter_T) + sum(cost_t(state_t, action_t; parameter_t))
states, actions
subject to      dynamics_t(state_t, action_t, state_t+1; parameter_t),         t = 1,...,T-1 
                constraint_t(state_t, action_t; parameter_t) {<,=} 0,          t = 1,...,T
                state_lower_t < state_t < state_upper_t,                       t = 1,...,T 
                action_lower_t < action_t < action_upper_t,                    t = 1,...,T-1.

with direct trajectory optimization.

Fast and allocation-free gradients and sparse Jacobians are automatically generated using Symbolics.jl for user-provided costs, constraints, and dynamics. The problem is solved with Ipopt.



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