def Reach(markers,milestones,n_steps,params):
    robot=params['robot']
    Q0=params['Q0']
    Q0inv=params['Q0inv']
    lower_lim=params['lower_lim']
    upper_lim=params['upper_lim']
    K_v=params['K_v']
    K_p=params['K_p']
    K_li=params['K_li']
    K_sr=params['K_sr']

    n_dof=robot.GetDOF()
    n_var=n_dof+6
    
    baselink=robot.GetLinks()[0]

    res=[]
    res.append(HRP4.GetConfig(robot))
    cur_config=res[0]

    with robot:

        for kk in range(len(milestones)):

            for step in range(n_steps):
                T=baselink.GetTransform()
                euler=HRP4.mat2euler(T[0:3,0:3])

                # Compute the Jacobians and desired velocities of the markers to follow
                J_markers=None
                v_desired=None
                for j in range(len(markers)):
                    # Jacobian
                    linkj=robot.GetLinks()[markers[j]['link_index']]
                    p_cur=dot(linkj.GetTransform(),add1(markers[j]['local_pos']))[0:3]
                    J_markers=concat([J_markers,Jacobian(euler,markers[j]['link_index'],p_cur,params)])

                    # velocity
                    p_end=markers[j]['p_vect'][:,milestones[kk]]
                    v_desired=concat([v_desired,(p_end-p_cur)/(n_steps-step)])

                # Find the out-of-range DOFs
                lower_list=[]
                upper_list=[]
                DOFvalues=robot.GetDOFValues()       
                for j in range(n_dof):
                    if DOFvalues[j]<lower_lim[j]:
                        lower_list.append(j)
                    elif DOFvalues[j]>upper_lim[j]:
                        upper_list.append(j)

                # Compute the Jacobians and the desired velocities for the out-of-range DOFs
                J_lower=zeros((n_var,n_var))
                v_lower=zeros(n_var)
                J_upper=zeros((n_var,n_var))
                v_upper=zeros(n_var)
                for i in lower_list:            
                    J_lower[6+i,6+i]=1
                    v_lower[6+i]=K_li*(lower_lim[i]-DOFvalues[i])
                for i in upper_list:
                    J_upper[6+i,6+i]=1
                    v_upper[6+i]=K_li*(upper_lim[i]-DOFvalues[i])
                J_limits=concat([J_lower,J_upper])
                v_limits=concat([v_lower,v_upper])

                # Inverse kinematics computations
                # J_main=J_markers
                # v_main=v_desired
                # J_aux=J_limits
                # v_aux=v_limits

                # J_main_star=dot(J_main,Q0inv)
                # J_main_star_dash=linalg.pinv(J_main_star)
                # J_weighted_pinv=dot(Q0inv,J_main_star_dash)
                # thetad_0=dot(J_weighted_pinv,v_main)
                # W=eye(n_var)-dot(J_weighted_pinv,J_main)

                # v_aux_0=dot(J_aux,thetad_0)
                # S=dot(J_aux,W)
                # [ms,ns]=shape(S)

                # delta_v_aux=v_aux-v_aux_0
                # Sstar=dot(transpose(S),linalg.inv(dot(S,transpose(S))+K_sr*eye(ms)))
                # y=dot(Sstar,delta_v_aux)

                # thetad=thetad_0+dot(W,y)


                J_main=concat([J_markers,J_limits])
                v_main=concat([v_desired,v_limits])

                J_main_star=dot(J_main,Q0inv)
                J_main_star_dash=linalg.pinv(J_main_star)
                J_weighted_pinv=dot(Q0inv,J_main_star_dash)
                thetad_0=dot(J_weighted_pinv,v_main)

                thetad=thetad_0

                cur_config=cur_config+thetad
                res.append(cur_config)
                HRP4.SetConfig(robot,cur_config)

    return Trajectory.SampleTrajectory(transpose(array(res)))
Beispiel #2
0





robot.GetLinks()[0].GetTransform()
robot.GetDOFValues()

PinAndDrag.thread_params=params
baselink=robot.GetLinks()[0]


# Initial
hrp.halfsit()
config=HRP4.GetConfig(robot)
p_init=robot.GetLinks()[18].GetGlobalCOM()
center=baselink.GetTransform()[0:3,3]
u=p_init-center
R0=HRP4.rpy2mat(config[3:6])


#Prediction
J=PinAndDrag.Jacobian(config[3:6],18,p_init)
delta=zeros(56)
delta[3:6]=1e-3*array([1,-1,2])
p_predicted=p_init+dot(J,delta)
config2=config+delta
R1=HRP4.rpy2mat(config2[3:6])
shift=dot(R1,u)
p_predicted2=center+shift
Beispiel #3
0
def Reach(linkindex,linkindex2,p_end,n_steps,params):
    robot=params['robot']
    Q0=params['Q0']
    Q0inv=params['Q0inv']
    lower_lim=params['lower_lim']
    upper_lim=params['upper_lim']
    K_v=params['K_v']
    K_p=params['K_p']
    K_li=params['K_li']
    K_sr=params['K_sr']

    n_dof=robot.GetDOF()
    n_var=n_dof+6
    
    baselink=robot.GetLinks()[0]

    res=[]
    res.append(HRP4.GetConfig(robot))
    cur_config=res[0]

    link2=robot.GetLinks()[linkindex2]

    with robot:

        for step in range(n_steps):
            T=baselink.GetTransform()
            euler=HRP4.mat2euler(T[0:3,0:3])

            # Compute the Jacobians and desired velocities of the markers to follow
            p_cur=link2.GetGlobalCOM()
            J_marker=FollowTrajectory.Jacobian(euler,linkindex,p_cur,params)

            v_desired=(p_end-p_cur)/(n_steps-step)

            # Find the out-of-range DOFs
            lower_list=[]
            upper_list=[]
            DOFvalues=robot.GetDOFValues()       
            for j in range(n_dof):
                if DOFvalues[j]<lower_lim[j]:
                    lower_list.append(j)
                elif DOFvalues[j]>upper_lim[j]:
                    upper_list.append(j)

            # Compute the Jacobians and the desired velocities for the out-of-range DOFs
            J_lower=zeros((n_var,n_var))
            v_lower=zeros(n_var)
            J_upper=zeros((n_var,n_var))
            v_upper=zeros(n_var)
            for i in lower_list:            
                J_lower[6+i,6+i]=1
                v_lower[6+i]=K_li*(lower_lim[i]-DOFvalues[i])
            for i in upper_list:
                J_upper[6+i,6+i]=1
                v_upper[6+i]=K_li*(upper_lim[i]-DOFvalues[i])
            J_limits=FollowTrajectory.concat([J_lower,J_upper])
            v_limits=FollowTrajectory.concat([v_lower,v_upper])


            J_main=FollowTrajectory.concat([J_marker,J_limits])
            v_main=FollowTrajectory.concat([v_desired,v_limits])

            J_main_star=dot(J_main,Q0inv)
            J_main_star_dash=linalg.pinv(J_main_star)
            J_weighted_pinv=dot(Q0inv,J_main_star_dash)
            thetad_0=dot(J_weighted_pinv,v_main)

            thetad=thetad_0

            cur_config=cur_config+thetad
            res.append(cur_config)
            HRP4.SetConfig(robot,cur_config)

    return cur_config
Beispiel #4
0
def IKreach(drag, pinned_links, p_end):
    global thread_params
    robot = thread_params['robot']
    p_step = thread_params['p_step']
    Q0 = thread_params['Q0']
    Q0inv = thread_params['Q0inv']
    lower_lim = thread_params['lower_lim']
    upper_lim = thread_params['upper_lim']
    K_li = thread_params['K_li']
    K_sr = thread_params['K_sr']

    ndof = robot.GetDOF()

    drag_link = drag[0]
    drag_type = drag[1]

    n_pins = len(pinned_links)
    baselink = robot.GetLinks()[0]

    link = robot.GetLinks()[drag_link]
    p_init = link.GetGlobalCOM()
    n_steps = norm(p_end - p_init) / p_step
    for steps in range(int(n_steps) + 1):
        p_cur = link.GetGlobalCOM()
        T = baselink.GetTransform()
        euler = HRP4.mat2euler(T[0:3, 0:3])

        # Compute the dragged link Jacobian
        if drag_type == 'translation':
            J_drag_a = Jacobian(euler, drag_link, p_cur)
            J_drag_b = Jacobian(euler, drag_link, p_cur + array([0, 0, 1]))
            J_drag_c = Jacobian(euler, drag_link, p_cur + array([0, 1, 0]))
            J_drag = concat([J_drag_a, J_drag_b, J_drag_c])
            (k, nvar) = shape(J_drag_a)
        else:
            J_drag = Jacobian(euler, drag_link, p_cur)
            (k, nvar) = shape(J_drag)

        # Compute the desired_velocity
        dist = norm(p_end - p_cur)
        if dist < p_step:
            v_drag_0 = p_end - p_cur
        else:
            v_drag_0 = (p_end - p_cur) / dist * p_step

        if drag_type == 'translation':
            v_drag = concat([v_drag_0, v_drag_0, v_drag_0])
        else:
            v_drag = v_drag_0

        # Compute the Jacobians and the desired velocities of the pins
        J_pins = None
        v_pins = None
        for i in range(n_pins):
            pinned_i = pinned_links[i]
            pinned_link = robot.GetLinks()[pinned_i]
            CoMi = pinned_link.GetGlobalCOM()
            J_pinned_ia = Jacobian(euler, pinned_i, CoMi)
            J_pinned_ib = Jacobian(euler, pinned_i, CoMi + array([0, 0, 1]))
            J_pinned_ic = Jacobian(euler, pinned_i, CoMi + array([0, 1, 0]))
            J_pins = concat([J_pins, J_pinned_ia, J_pinned_ib, J_pinned_ic])
            v_pins = concat([v_pins, zeros(3 * k)])

        # Find the out-of-range DOFs
        lower_list = []
        upper_list = []
        DOFvalues = robot.GetDOFValues()
        for j in range(ndof):
            if DOFvalues[j] < lower_lim[j]:
                lower_list.append(j)
            elif DOFvalues[j] > upper_lim[j]:
                upper_list.append(j)

        # Compute the Jacobians and the desired velocities for the out-of-range DOFs
        J_lower = zeros((nvar, nvar))
        v_lower = zeros(nvar)
        J_upper = zeros((nvar, nvar))
        v_upper = zeros(nvar)
        for i in lower_list:
            J_lower[6 + i, 6 + i] = 1
            v_lower[6 + i] = K_li * (lower_lim[i] - DOFvalues[i])
        for i in upper_list:
            J_upper[6 + i, 6 + i] = 1
            v_upper[6 + i] = K_li * (upper_lim[i] - DOFvalues[i])
        J_limits = concat([J_lower, J_upper])
        v_limits = concat([v_lower, v_upper])

        # Computations
        if thread_params['priority'] == 'drag':
            J_main = J_drag
            v_main = v_drag
            J_aux = J_pins
            v_aux = v_pins
        else:
            J_main = J_pins
            v_main = v_pins
            J_aux = J_drag
            v_aux = v_drag

        J_aux = concat([J_aux, J_limits])
        v_aux = concat([v_aux, v_limits])

        if J_main != None:
            J_main_star = dot(J_main, Q0inv)
            J_main_star_dash = linalg.pinv(J_main_star)
            J_weighted_pinv = dot(Q0inv, J_main_star_dash)
            thetad_0 = dot(J_weighted_pinv, v_main)
            W = eye(nvar) - dot(J_weighted_pinv, J_main)
        else:
            thetad_0 = zeros(nvar)
            W = eye(nvar)

        v_aux_0 = dot(J_aux, thetad_0)
        S = dot(J_aux, W)
        [ms, ns] = shape(S)

        delta_v_aux = v_aux - v_aux_0
        Sstar = dot(transpose(S),
                    linalg.inv(dot(S, transpose(S)) + K_sr * eye(ms)))
        y = dot(Sstar, delta_v_aux)

        thetad = thetad_0 + dot(W, y)

        HRP4.SetConfig(robot, HRP4.GetConfig(robot) + thetad)

        #Update the positions of the spheres
        for i in range(robot.GetDOF()):
            if not (i in thread_params['exclude_list']):
                UpdateSphere(i)

        #Draw the COM
        if thread_params['draw_com']:
            #try:
            #    params['com_handle']=None
            #except AttributeError:
            #    pass
            CoM = ZMP.ComputeCOM([
                robot.GetLinks()[0].GetTransform()[0:3, 3],
                robot.GetDOFValues()
            ], {
                'robot': robot,
                'exclude_list': []
            })
            CoM_proj = zeros(3)
            CoM_proj[0] = CoM[0]
            CoM_proj[1] = CoM[1]
            thread_params['com_handle'] = robot.GetEnv().drawlinestrip(
                array([CoM, CoM_proj]), 5)

        time.sleep(thread_params['timestep'])