Segmentation violation in ocp_create with MATLAB

Hi.

I have been trying to port the race_cars example to MATLAB but am currently struggling during code generation which leads to the following stack violation:

    Configuration:
      Crash Decoding           : Disabled - No sandbox or build area path
      Crash Mode               : continue (default)
      Default Encoding         : UTF-8
      Deployed                 : false
      Desktop Environment      : ubuntu:GNOME
      GNU C Library            : 2.27 stable
      Graphics Driver          : Unknown hardware 
      Graphics card 1          : 0x10de ( 0x10de ) 0x1fb8 Version 440.33.1.0 (0-0-0)
      Graphics card 2          : 0x8086 ( 0x8086 ) 0x3e9b Version 0.0.0.0 (0-0-0)
      Java Version             : Java 1.8.0_202-b08 with Oracle Corporation Java HotSpot(TM) 64-Bit Server VM mixed mode
      MATLAB Architecture      : glnxa64
      MATLAB Entitlement ID    : 6428867
      MATLAB Root              : /usr/local/MATLAB/R2019b
      MATLAB Version           : 9.7.0.1296695 (R2019b) Update 4
      OpenGL                   : hardware
      Operating System         : Ubuntu 18.04.4 LTS
      Process ID               : 29842
      Processor ID             : x86 Family 6 Model 158 Stepping 13, GenuineIntel
      Session Key              : 96c58266-4b3a-4410-954f-77f2426cc916
      Static TLS mitigation    : Enabled: Full
      Window System            : The X.Org Foundation (12005000), display :0

    Fault Count: 5


    Abnormal termination:
    Segmentation violation

    Register State (from fault):
      RAX = 0000000000000000  RBX = 00007fa10e727020
      RCX = 0000000000000005  RDX = 0000000000000007
      RSP = 00007fa38bff9d00  RBP = 00007fa38bffa110
      RSI = 0000000000000000  RDI = 00007fa10e727020

       R8 = 00007fa38bff9b90   R9 = 00007fa29df705ec
      R10 = 00007fa29f746d08  R11 = 00007fa29f746dd4
      R12 = 00007fa29f741c50  R13 = 00007fa29df56090
      R14 = 00007fa2748cdde0  R15 = 0000000000000032

      RIP = 00007fa10e720619  EFL = 0000000000010206

       CS = 0033   FS = 0000   GS = 0000

    Stack Trace (from fault):
    [  0] 0x00007fa10e720619 /home/thomas/build/ocp_create.mexa64+00009753 mexFunction+00005193
    [  1] 0x00007fa397eb6de3     /usr/local/MATLAB/R2019b/bin/glnxa64/libmex.so+00548323
    [  2] 0x00007fa397eb6ee5     /usr/local/MATLAB/R2019b/bin/glnxa64/libmex.so+00548581
    [  3] 0x00007fa397eb7317     /usr/local/MATLAB/R2019b/bin/glnxa64/libmex.so+00549655
    [  4] 0x00007fa397eb7f93     /usr/local/MATLAB/R2019b/bin/glnxa64/libmex.so+00552851
    [  5] 0x00007fa397ea37ac     /usr/local/MATLAB/R2019b/bin/glnxa64/libmex.so+00468908
    [  6] 0x00007fa398cd815f /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_dispatcher.so+01073503 _ZN8Mfh_file20dispatch_file_commonEMS_FviPP11mxArray_tagiS2_EiS2_iS2_+00000207
    [  7] 0x00007fa398cd9c5e /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_dispatcher.so+01080414
    [  8] 0x00007fa398cda1a1 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_dispatcher.so+01081761 _ZN8Mfh_file8dispatchEiPSt10unique_ptrI11mxArray_tagN6matrix6detail17mxDestroy_deleterEEiPPS1_+00000033
    [  9] 0x00007fa396373323 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+14025507
    [ 10] 0x00007fa3963780d6 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+14045398
    [ 11] 0x00007fa39647eebe /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+15122110
    [ 12] 0x00007fa396472211 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+15069713
    [ 13] 0x00007fa3963dee34 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+14466612
    [ 14] 0x00007fa39640544d /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+14623821
    [ 15] 0x00007fa395b8483b /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+05707835
    [ 16] 0x00007fa395b86a74 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+05716596
    [ 17] 0x00007fa395b8381d /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+05703709
    [ 18] 0x00007fa395b70cf1 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+05627121
    [ 19] 0x00007fa395b70f29 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+05627689
    [ 20] 0x00007fa395b83026 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+05701670
    [ 21] 0x00007fa395b83126 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+05701926
    [ 22] 0x00007fa395cbcc49 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+06986825
    [ 23] 0x00007fa395cc0383 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+07000963
    [ 24] 0x00007fa39622f0f1 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+12697841
    [ 25] 0x00007fa3963608a1 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+13949089
    [ 26] 0x00007fa39636199d /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+13953437
    [ 27] 0x00007fa398cd815f /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_dispatcher.so+01073503 _ZN8Mfh_file20dispatch_file_commonEMS_FviPP11mxArray_tagiS2_EiS2_iS2_+00000207
    [ 28] 0x00007fa398cd9c5e /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_dispatcher.so+01080414
    [ 29] 0x00007fa398cda1a1 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_dispatcher.so+01081761 _ZN8Mfh_file8dispatchEiPSt10unique_ptrI11mxArray_tagN6matrix6detail17mxDestroy_deleterEEiPPS1_+00000033
    [ 30] 0x00007fa396373323 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+14025507
    [ 31] 0x00007fa3963780d6 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+14045398
    [ 32] 0x00007fa39647eebe /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+15122110
    [ 33] 0x00007fa39647236c /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+15070060
    [ 34] 0x00007fa3963dee34 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+14466612
    [ 35] 0x00007fa39640547d /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+14623869
    [ 36] 0x00007fa395b8483b /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+05707835
    [ 37] 0x00007fa395b86a74 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+05716596
    [ 38] 0x00007fa395b8381d /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+05703709
    [ 39] 0x00007fa395b70cf1 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+05627121
    [ 40] 0x00007fa395b70f29 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+05627689
    [ 41] 0x00007fa395b83026 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+05701670
    [ 42] 0x00007fa395b83126 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+05701926
    [ 43] 0x00007fa395cbcc49 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+06986825
    [ 44] 0x00007fa395cc0383 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+07000963
    [ 45] 0x00007fa39622f0f1 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+12697841
    [ 46] 0x00007fa3961d9693 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+12347027
    [ 47] 0x00007fa3961ddd2f /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+12365103
    [ 48] 0x00007fa3961e10e2 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+12378338
    [ 49] 0x00007fa39627df8f /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+13021071
    [ 50] 0x00007fa39627e279 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwm_lxe.so+13021817
    [ 51] 0x00007fa397f464c4 /usr/local/MATLAB/R2019b/bin/glnxa64/libmwbridge.so+00341188 _Z8mnParserv+00000596
    [ 52] 0x00007fa398e235b5   /usr/local/MATLAB/R2019b/bin/glnxa64/libmwmcr.so+01017269
    [ 53] 0x00007fa3adb2242b   /usr/local/MATLAB/R2019b/bin/glnxa64/libmwmvm.so+03097643 _ZN14cmddistributor15PackagedTaskIIP10invokeFuncIN7mwboost8functionIFvvEEEEENS2_10shared_ptrINS2_13unique_futureIDTclfp_EEEEEERKT_+00000059
    [ 54] 0x00007fa3adb22518   /usr/local/MATLAB/R2019b/bin/glnxa64/libmwmvm.so+03097880 _ZNSt17_Function_handlerIFN7mwboost3anyEvEZN14cmddistributor15PackagedTaskIIP10createFuncINS0_8functionIFvvEEEEESt8functionIS2_ET_EUlvE_E9_M_invokeERKSt9_Any_data+00000024
    [ 55] 0x00007fa398f7389c   /usr/local/MATLAB/R2019b/bin/glnxa64/libmwiqm.so+00751772 _ZN7mwboost6detail8function21function_obj_invoker0ISt8functionIFNS_3anyEvEES4_E6invokeERNS1_15function_bufferE+00000028
    [ 56] 0x00007fa398f73557   /usr/local/MATLAB/R2019b/bin/glnxa64/libmwiqm.so+00750935 _ZN3iqm18PackagedTaskPlugin7executeEP15inWorkSpace_tag+00000439
    [ 57] 0x00007fa398e12015   /usr/local/MATLAB/R2019b/bin/glnxa64/libmwmcr.so+00946197
    [ 58] 0x00007fa398f586a0   /usr/local/MATLAB/R2019b/bin/glnxa64/libmwiqm.so+00640672
    [ 59] 0x00007fa398f3ce01   /usr/local/MATLAB/R2019b/bin/glnxa64/libmwiqm.so+00527873
    [ 60] 0x00007fa398f3da7f   /usr/local/MATLAB/R2019b/bin/glnxa64/libmwiqm.so+00531071
    [ 61] 0x00007fa398df9575   /usr/local/MATLAB/R2019b/bin/glnxa64/libmwmcr.so+00845173
    [ 62] 0x00007fa398df9b93   /usr/local/MATLAB/R2019b/bin/glnxa64/libmwmcr.so+00846739
    [ 63] 0x00007fa398dfa404   /usr/local/MATLAB/R2019b/bin/glnxa64/libmwmcr.so+00848900
    [ 64] 0x00007fa3abdf7bdd /usr/local/MATLAB/R2019b/bin/glnxa64/libmwboost_thread.so.1.65.1+00080861
    [ 65] 0x00007fa3acdc46db              /lib/x86_64-linux-gnu/libpthread.so.0+00030427
    [ 66] 0x00007fa3ac54da3f                    /lib/x86_64-linux-gnu/libc.so.6+01186367 clone+00000063
    [ 67] 0x0000000000000000                                   <unknown-module>+00000000

    This error was detected while a MEX-file was running. If the MEX-file
    is not an official MathWorks function, please examine its source code
    for errors. Please consult the External Interfaces Guide for information
    on debugging MEX-files.

The part of the MATLAB code that I use to define the Acados solver is included below:

    clear all
    import casadi.*

    %% Solver parameters
    nlp_solver = 'sqp'; % sqp, sqp_rti
    qp_solver = 'partial_condensing_hpipm';
        % full_condensing_hpipm, partial_condensing_hpipm, full_condensing_qpoases
    qp_solver_cond_N = 5; % for partial condensing
    % integrator type
    sim_method = 'erk'; % erk, irk, irk_gnsf

    %% horizon parameters
    N = 50;
    T = 1.0; % time horizon length

    %% model dynamics
    [model, constraint] = bicycle_model(track_file);

    nx = length(model.x);
    nu = length(model.u);

    %% model to create the solver
    ocp_model = acados_ocp_model();

    %% acados ocp model
    ocp_model.set('name', model.name);
    ocp_model.set('T', T);

    % symbolics
    ocp_model.set('sym_x', model.x);
    ocp_model.set('sym_u', model.u);
    ocp_model.set('sym_xdot', model.xdot);
    ocp_model.set('sym_z', model.z);
    ocp_model.set('sym_p', model.p);

    % dynamics
    if (strcmp(sim_method, 'erk'))
        ocp_model.set('dyn_type', 'explicit');
        ocp_model.set('dyn_expr_f', model.f_expl_expr);
    else % irk irk_gnsf
        ocp_model.set('dyn_type', 'implicit');
        ocp_model.set('dyn_expr_f', model.f_impl_expr);
    end

    % constraintsJbx = zeros(1,nx);
    nbx = 1;
    Jbx(nbx,2) = 1;
    ocp_model.set('constr_Jbx', Jbx);
    ocp_model.set('constr_lbx', [-12]);
    ocp_model.set('constr_ubx', [12]);

    nbu = 2;
    Jbu = zeros(nbu,nu);
    Jbu(1,1) = 1;
    Jbu(2,2) = 1;
    ocp_model.set('constr_Jbu', Jbu);
    ocp_model.set('constr_lbu', [model.dthrottle_min, model.ddelta_min]);
    ocp_model.set('constr_ubu', [model.dthrottle_max, model.ddelta_max]);

    %ocp_model.set('constr_type', 'bgh');
    ocp_model.set('constr_expr_h', constraint.expr);
    ocp_model.set('constr_lh', [...
                                    constraint.along_min,...
                                    constraint.alat_min,...
                                    model.n_min,...
                                    model.throttle_min,...
                                    model.delta_min,...
                                ]);
    ocp_model.set('constr_uh', [...
                                    constraint.along_max,...
                                    constraint.alat_max,...
                                    model.n_max,...
                                    model.throttle_max,...
                                    model.delta_max,...
                                ]);    
    %ocp_model.set('constr_expr_h_e', constraint.expr);     
    %ocp_model.set('constr_lh_e', 0);
    %ocp_model.set('constr_uh_e', 0);
                            
    %ocp.constraints.idxsh = np.array([0, 2])
    % Upper and lower bounds on slacks, are zero by default.
    % ocp.constraints.lsh = np.zeros(ocp.dims.nsh)
    % ocp.constraints.ush = np.zeros(ocp.dims.nsh)

    % set intial condition
    ocp_model.set('constr_x0', model.x0);

    % cost = define linear cost on x and u
    %ocp_model.set('cost_expr_ext_cost', model.expr_ext_cost);
    %ocp_model.set('cost_expr_ext_cost_e', model.expr_ext_cost_e);
    ocp_model.set('cost_type', 'linear_ls');
    ocp_model.set('cost_type_e', 'linear_ls');

    % number of outputs is the concatenation of x and u
    ny = nx + nu;
    ny_e = nx;

    % The linear cost contributions is defined through Vx, Vu and Vz
    Vx = zeros(ny, nx);
    Vx_e = zeros(ny_e, nx);
    Vu = zeros(ny, nu);

    Vx(1:nx,:) = eye(nx);
    Vx_e(1:nx,:) = eye(nx);
    Vu(nx+1:end,:) = eye(nu);
    ocp_model.set('cost_Vx', Vx);
    ocp_model.set('cost_Vx_e', Vx_e);
    ocp_model.set('cost_Vu', Vu);

    % Define cost on states and input
    Q = diag([ 1e-1, 1e-8, 1e-8, 1e-8, 1e-3, 5e-3 ]);
    R = eye(nu);
    R(1, 1) = 1e-3;
    R(2, 2) = 5e-3;
    Qe = diag([ 5e0, 1e1, 1e-8, 1e-8, 5e-3, 2e-3 ]);

    unscale = N / T;
    W = unscale * blkdiag(Q, R);
    W_e = Qe / unscale;
    ocp_model.set('cost_W', W);
    ocp_model.set('cost_W_e', W_e);

    % set intial references
    y_ref = zeros(ny,1);
    y_ref_e = zeros(ny_e,1);
    y_ref(1) = 1; % set reference on 's' to 1 to push the car forward (progress)
    ocp_model.set('cost_y_ref', y_ref);
    ocp_model.set('cost_y_ref_e', y_ref_e);

    % Set dimensions
    ocp_model.set('dim_nx', nx);
    ocp_model.set('dim_nu', nu);
    ocp_model.set('dim_ny', ny);
    ocp_model.set('dim_ny_e', ny_e);
    ocp_model.set('dim_nbx', nbx);
    ocp_model.set('dim_nbu', nbu);

    % ... see ocp_model.model_struct to see what other fields can be set

    %% acados ocp set opts
    ocp_opts = acados_ocp_opts();
    ocp_opts.set('param_scheme_N', N);
    ocp_opts.set('nlp_solver', nlp_solver);
    ocp_opts.set('nlp_solver_exact_hessian', false); % false=gauss_newton, true=exact
    ocp_opts.set('sim_method', sim_method);
    ocp_opts.set('sim_method_num_stages', 4);
    ocp_opts.set('sim_method_num_steps', 3);
    ocp_opts.set('qp_solver', qp_solver);
    %ocp_opts.set('qp_solver_cond_N', qp_solver_cond_N);
    %ocp_opts.set('nlp_solver_tol_stat', 1e-4);
    %ocp_opts.set('nlp_solver_tol_eq', 1e-4);
    %ocp_opts.set('nlp_solver_tol_ineq', 1e-4);
    %ocp_opts.set('nlp_solver_tol_comp', 1e-4);
    % ... see ocp_opts.opts_struct to see what other fields can be set

    %% create ocp solver
    ocp = acados_ocp(ocp_model, ocp_opts);

In the model definition I am using CasADi MX objects? Would that matter?
I am also using GCC 7.4.0 but I am able to compile and run the other MATLAB examples without any problems.

Any clues?

Best regards
Thomas Jespersen

Problem solved: Avoid spaces in your paths!

I also noticed that I would get a more elaborate error message by enabling:

ocp_opts.set('compile_interface', 'auto');
ocp_opts.set('codgen_model', 'true');

Hi @mindthomas,

I just added a check for empty spaces in the path.


I guess this solved your problem.

Good luck with the race cars for Matlab!
If you manage to do this and a PR with this Matlab example would be very welcome also :slight_smile:

Best,
Jonathan

Thanks Jonathan. I’m sure that will help against future frustrated users :wink:
Although I don’t know if it is only applicable to Unix users?

I have already opened a PR with the a ported version of the race cars example: https://github.com/acados/acados/pull/629/

I remember, there was also a problem on Windows.
I guess it is good to have a general check for that.

Great, I will comment on the PRs.
Marking this one here as solved.