* 10s lat
* Full length MPC
* redfine N
* Leave controls the same for now
* Updates
* use long plan in lat plan
* interp plan
* add new interp
* simplergit add selfdrive/controls/plannerd.py selfdrive/controls/
* expand to 10s
* revert this
* fix linter
* Update sconscripts
* fix test
* fix test
* fix test
* Revert "Update sconscripts"
This reverts commit 6e23c69dce.
* Dont import drive helpers
* better compile deps
* fix compile
* comment
* update replay
* Update plannerd time
* Add explicit cost on steering wheel movement
* Laxer low speed control
* Laxer low speed control
* Lower min speed now there is a cost
* 3m/s
* Similar to old master
* Add cost
* Crazy high
* Update ref
* comment
* lat_mpc: make v_ego, rotation_radius parameters instead of states
* lat_mpc: remove rotation_radius argument, since it is part of the parameters
* lat_mpc: use qp_solver_cond_N = 1
slightly faster and in line with case study in Fig. 2/ 3 in Frison2016 - https://cdn.syscop.de/publications/Frison2016.pdf
An Efficient Implementation of Partial Condensing for Nonlinear Model Predictive Control
* adapt test_lateral_mpc to formulation with parameters
* lat_mpc: set parameters in reset() and copy values
* acados_ocp_solver_pyx: make options_set useable
* update ref
Co-authored-by: Willem Melching <willem.melching@gmail.com>
* no heading cost
* live mpc weight config
* need to add stds
* make work on empty data
* no divide by 0
* update refs
* update model replay
* update proc replat
* new model replay ref
* start again
* need that too
* this actually works
* not needed
* do properly
* still works
* still works
* still good
* all G without ll
* still works
* all still good
* cleanup building
* cleanup sconscript
* new lane planner
* how on earth is this silent too....
* update
* add rotation radius
* update
* pathplanner first pass
* misc fixes
* fix
* need deep_interp
* local again
* fix
* fix test
* very old
* new replay
* interp properly
* correct length
* another horrible silent bug
* like master
* fix that
* do doubles
* different delay compensation
* make robust to empty msg
* make pass with hack for now
* add some extra
* update ref for increased leg
* test cpu usage on this pr
* tiny bit faster
* purge numpy
* update ref
* not needed
* ready for merge
* try again after recompile
Co-authored-by: Adeeb Shihadeh <adeebshihadeh@gmail.com>
cl0cks4fe
Adeeb Shihadeh
Harald Schäfer
Jonathan Frey
BRose98
George Hotz