  Rehabilitation tasks demand robust and accurate trajectory-tracking
performance, mainly achieved with parallel robots. In this field, limiting the
value of the force exerted on the patient is crucial, especially when an
injured limb is involved. In human-robot interaction studies, the admittance
controller modifies the location of the robot according to the user efforts
driving the end-effector to an arbitrary location within the workspace.
However, a parallel robot has singularities within the workspace, making
implementing a conventional admittance controller unsafe. Thus, this study
proposes an admittance controller that overcomes the limitations of singular
configurations by using a real-time singularity avoidance algorithm. The
singularity avoidance algorithm modifies the original trajectory based on the
actual location of the parallel robot. The complemented admittance controller
is applied to a 4 degrees of freedom parallel robot for knee rehabilitation. In
this case, the actual location is measured by a 3D tracking system because the
location calculated by the forward kinematics is inaccurate in the vicinity of
a singularity. The experimental results verify the effectiveness of the
proposed admittance controller for safe knee rehabilitation exercises
