Code
Version 0.7.2 is now available. Download.
Package Overview
Demo (1 file)
main_demo.m
Numerical Methods (5 files)
public:
revise_grad.m
revise_dls.m
revise_newton.m
private:
revise_plot.m
jacobian3cc.m
Quaternion Operations (3 files)
up_plus.m
up_oplus.m
up_star.m
Solver (7 files)
public:
micsolver.m
micsolverd.m
private:
rho.m
soln2xi.m
get_err.m
solve_r1.m
solve_r2.m
Lie Algebra Operations (4 files)
up_hat.m
up_vee.m
exphat.m
veelog.m
Conversions (6 files)
arc2q.m
q2arc.m
arc2xi.m
xi2arc.m
rot2q.m
q2rot.m
Other Tools (4 files)
circles3.m
get_end.m
collision_indicator.m
collision_marker.m
Functions
Solver
micsolver.m
MICSOLVER Multi-solution solver for the inverse kinematics of 3-section constant-curvature robots.
[NOS, NOI] = MICSOLVER(L1, L2, L3, Q, R, TOL, IS_A_SOL) returns the result of solving the 3-section inverse kinematics problem. The function uses preset resolutions or numerical methods to address the inverse kinematics problem. The function exits after one solution is found.
Input parameters
L1, L2, L3 section length
Q, R desired end rotation and translation
TOL error tolerance
IS_A_SOL function handle
It is used to judge if the given parameter is a solution to the inverse kinematics problem.
The function has two inputs (ERR, XI) and one output in boolean type.
Output parameters
NOS number of solutions
NOI number of iterations in numerical correction
Example
L1 = 1; L2 = 1; L3 = 1;
xi = arc2xi(L1, L2, L3, pi.*[1,2,1,2,1,2].*rand(1, 6));
T = get_end(L1, L2, L3, xi);
q = rot2q(T(1:3, 1:3));
r = T(1:3, 4);
tol = 1e-2; fun = @(e, x) e < tol;
tic;
[nos, ~] = micsolver(L1, L2, L3, q, r, tol, fun);
rt = toc*1000;
if nos
    fprintf('A solution is found in %.2f ms.\n', rt);
end
micsolverd.m
MICSOLVERD Multi-solution solver (debug) for the inverse kinematics of 3-section constant-curvature robots.
[SOL, NOS, NOI] = MICSOLVERD(L1, L2, L3, Q, R, PAR, NOC, TOL, MSTEP, IS_A_SOL, PLOT_EC, PLOT_IT)Â returns the result of solving the 3-section inverse kinematics problem.
Input parameters
L1, L2, L3 section length
Q, R desired end rotation and translation
PAR length of the partition
Scalar. The interval $[0, 1)$ is partitioned into subintervals with length PAR. A smaller
PAR means finer resolution. We recommend PAR = 0.03 for better efficiency and
PAR = 0.01 for more solutions.
NOC number of corrections
A 1-by-2 array. The model parameters $\hat{\boldsymbol{r}}_3$ and hat
$\hat{\boldsymbol{r}}_1$ are corrected for NOC(1) and NOC(2) times after the
approximation, respectively. Large NOC provides closer initial value and more
computations. We recommend NOC = [1, 2] for better efficiency and
NOC = [5, 5] for better estimation. Â
TOL error tolerance Â
MSTEP allowed maximum steps of iterations Â
IS_A_SOL function handle Â
This function is used to judge if the given parameter is a solution to the inverse kinematics
problem. The function has two inputs (ERR, XI) and one output in boolean type. Â
PLOT_EC set 'plot' to visualise the traversal Â
PLOT_IT set 'plot' to visualise the numerical correction
Output parameters
SOL solutions Â
A 6-by-NOS array. Each column is the overall exponential coordinate XI. Â
NOS number of solutions Â
NOI number of iterations in numerical correction
Example
L1 = 1; L2 = 1; L3 = 1;
alpha = 15*pi/16; omega = [0.48; sqrt(3)/10; -0.86];
q = [cos(alpha/2); sin(alpha/2)*omega];
r = [-0.4; 1.1; 0.8];
tol = 1e-2; fun = @(e, x) e < tol;
[sol, ~, ~] = micsolverd(L1, L2, L3, q, r, ...
                         0.01, [5, 5], tol, 10, fun, ...
                         'plot', 'plot');
for eta = 1: size(sol, 2)
    fh = figure();
    circles3(fh, L1, L2, L3, sol(:, eta), 'k-');
    view(119, 20);
end
rho.m
RHO Computes the linear distance between two ends of a circular arc.
This is a private function of our solver.
soln2xi.m
SOLN2XI Converts the output of our solver to an exponential coordinate.
This is a private function of our solver.
get_err.m
GET_ERR Computes the error between desired and current end pose.
This is a private function of our solver.
solve_r1.m
SOLVE_R1 Computes the model parameter of the 1st section.
This is a private function of our solver.
solve_r2.m
SOLVE_R2 Computes the model parameter of the 2nd section using rotational and translational constraints.
This is a private function of our solver.
Numerical Methods
revise_grad.m & revise_dls.m & revise_newton.m
REVISE_* Correct the initial value with a numerical method.
[XI_STAR, ERR, K] = REVISE_*(L1, L2, L3, Q, R, XI, MSTEP, TOL, TYPE) returns the result of numerical correction.
Methods
grad gradient method
dls damped least square method
newton Newton-Raphson method
Input parameters
L1, L2, L3 section length
Q, R desired end rotation and translation
XI initial value
MSTEP allowed maximum steps of iterations
TOL error tolerance
TYPE set 'plot' to visualise the numerical correction
Output parameters
XI_STAR final value
ERR final error
K steps of iterations
Example
L1 = 1; L2 = 1; L3 = 1;
alpha = 15*pi/16; omega = [0.48; sqrt(3)/10; -0.86];
q = [cos(alpha/2); sin(alpha/2)*omega];
r = [-0.4; 1.1; 0.8];
xi_0 = arc2xi(L1, L2, L3, pi.*[1, 2, 1, 2, 1, 2].*rand(1, 6));
[xi, err, noi] = revise_grad(L1, L2, L3, q, r, xi_0, 2000, 1e-2, 'plot');
[xi, err, noi] = revise_dls(L1, L2, L3, q, r, xi_0, 2000, 1e-2, 'plot');
[xi, err, noi] = revise_newton(L1, L2, L3, q, r, xi_0, 200, 1e-2, 'plot');
revise_plot.m
REVISE_PLOT Visualises the numerical correction.
This is a private function of numerical methods.
jacobian3cc.m
JACOBIAN3CC Computes the Jacobian matrix when the forward kinematics is expressed by the product of exponentials formula.
J = JACOBIAN3CC(L1, L2, L3, XI) returns the 6-by-6 Jacobian matrix.
Quaternion Operations
up_plus.m
UP_PLUS Computes the matrix for left multiplications of quaternions.
Q_UP_PLUS = UP_PLUS(Q) returns the left multiplication matrix of Q.
up_oplus.m
UP_OPLUS Computes the matrix for right multiplications of quaternions.
Q_UP_OPLUS = UP_OPLUS(Q) returns the right multiplication matrix of Q.
up_star.m
UP_STAR Computes the quaternion conjugation.
Q_UP_STAR = UP_STAR(Q) returns the conjugation of Q.
Lie Algebra Operations
up_hat.m
UP_HAT Computes the Lie algebra of a vector.
M = UP_HAT(V) is an element of $\mathsf{so}_3$ or $\mathsf{se}_3$, where V is an element of $\mathbb{R}^3$ or $\mathbb{R}^6$, respectively.
up_vee.m
UP_VEE Computes the vector of a Lie algebra.
V = UP_VEE(M) is an element of $\mathbb{R}^3$ or $\mathbb{R}^6$, where M is an element of $\mathsf{so}_3$ or $\mathsf{se}_3$, respectively.
exphat.m
EXPHAT Composition of the hat map and the matrix exponential.
M = EXPHAT(V) is a matrix in $\mathsf{SO}_3$ or $\mathsf{SE}_3$ and is computed using Rodrigues' formula. The vector V is in $\mathbb{R}^3$ or $\mathbb{R}^4$. The hat map sends V to an element of $\mathsf{so}_3$ or $\mathsf{se}_3$.
veelog.m
VEELOG Composition of the matrix logarithm and the vee map.
V = VEELOG(M) is a vector in $\mathbb{R}^3$ or $\mathbb{R}^4$ and is computed using Rodrigues' formula. The matrix M is in $\mathsf{SO}_3$ or $\mathsf{SE}_3$. The vee map sends an element of $\mathsf{so}_3$ or $\mathsf{se}_3$ to a vector.
Conversions
arc2q.m
ARC2Q Converts arc parameters to a quaternion.
Q = ARC2Q(KAPPA, PHI, L) computes the quaternion Q representing the end rotation of a 1-section constant-curvature robot with curvature KAPPA, bending angle PHI, and section length L.
Example
kappa = 2*pi/3;
phi = pi/3;
q = arc2q(kappa, phi, 1);
q2arc.m
Q2ARC Converts a quaternion to arc parameters.
ARC = Q2ARC(Q, L) computes the arc parameters of a 1-section constant-curvature robot, including the curvature KAPPA and bending angle PHI. The section length is L. The quaternion Q represents the end rotation.
Example
q = [1/2; -3/4; sqrt(3)/4; 0];
arc = q2arc(q, 1);
arc2xi.m
ARC2XI Converts the arc parameters of 3 sections to the exponential coordinate.
XI = ARC2XI(L1, L2, L3, ARC) computes the exponential coordinate XI of a 3-section constant-curvature robot. The section lengths are L1, L2 and L3, respectively. The parameter ARC is an array containing curvatures and bending angles of each section.
Example
k1 = 4*sqrt(5)/5; p1 = atan(2);
k2 = sqrt(37)/5; p2 = -pi+atan(6);
k3 = sqrt(10)/5; p3 = -atan(3);
xi = arc2xi(1, 1, 1, [k1, p1, k2, p2, k3, p3]);
xi2arc.m
XI2ARC Converts the exponential coordinate to the arc parameters of 3 sections.
ARC = XI2ARC(L1, L2, L3, XI) computes the arc parameter ARC of a 3-section constant-curvature robot. The section lengths are L1, L2 and L3, respectively. The parameter XI is the overall exponential coordinate.
Example
xi = [-1.6; 0.8; 1.2; -0.2; 0.6; 0.2];
arc = xi2arc(1, 1, 1, xi);
q2rot.m
Q2ROT Converts a quaternion to a rotation matrix.
R = Q2ROT(Q) returns the rotation matrix that is equivalent to the quaternion.
rot2q.m
ROT2Q Converts a rotation matrix to a quaternion.
Q = ROT2Q(R) returns the quaternion that is equivalent to the rotation matrix.
Other Tools
circles3.m
CIRCLES3 Visualises the 3-section constant-curvature robot with given model parameters.
CIRCLES3(FH, L1, L2, L3, XI, TYPE) displays the plot in target figure FH. The robot is described by the section lengths L1, L2, L3 and the overall exponential coordinate XI. Line colours and styles are specified in the character string TYPE.
Example
L1 = 1; L2 = 1; L3 = 1;
xi_1 = [-1.60; 0.08; 1.20; -0.20; 0.60; 0.20];
circles3(1, L1, L2, L3, xi_1, 'k--');
xi_2 = [-0.39; 0.48; -1.13; 0.47; 1.79; -0.17];
circles3(1, L1, L2, L3, xi_2, 'k-');
view(75, 9);
get_end.m
GET_END Computes the end pose of a 3-section constant-curvature robot.
T = GET_END(L1, L2, L3, XI) returns the 4-by-4 matrix of end pose.
Example
xi = [-1.6; 0.8; 1.2; -0.2; 0.6; 0.2];
T = get_end(1, 1, 1, xi);
collision_indicator.m
COLLISION_INDICATOR Computes the minimal distance between the sample points and the spherical obstacles.
COLLIDE = COLLISION_INDICATOR(L1, L2, L3, XI, RO, ROR, SMP) returns the minimal distance COLLIDE. If COLLIDE > 0, then no collision occurs. If COLLIDE < 0, then the robot collides with obstacles. The robot is described by the section lengths L1, L2, L3 and the overall exponential coordinate XI. The obstacles are spheres centring at RO with radius ROR. The sample points are distributed uniformly along the robot curve with the number SMP.
Example
L1 = 1; L2 = 1; L3 = 1;
xi = [-1.6; 0.8; 1.2; -0.2; 0.6; 0.2];
ro = [0.8; 0.7; 0.6];
ror = 0.4;
collide = collision_indicator(L1, L2, L3, xi, ro, ror, 10);
collision_marker.m
COLLISION_MARKER Visualises the collision part in yellow.
COLLISION_MARKER(L1, L2, L3, XI, RO, ROR) draws the part of the robot that is collided with obstacles. The robot is described by the section lengths L1, L2, L3 and the overall exponential coordinate XI. The obstacles are spheres centring at RO with radius ROR.
Example
L1 = 1; L2 = 1; L3 = 1;
xi = [-1.6; 0.8; 1.2; -0.2; 0.6; 0.2];
ro = [0.8; 0.7; 0.6];
ror = 0.4;
circles3(1, L1, L2, L3, xi, 'k-');
collision_marker(L1, L2, L3, xi, ro, ror);
view(75, 9);