  The application of biomechanic and motor control models in the control of
bidedal robots (humanoids, and exoskeletons) has revealed limitations of our
understanding of human locomotion. A recently proposed model uses the potential
energy for bipedal structures to model the bipedal dynamics, and it allows to
predict the system dynamics from its kinematics. This work proposes a
task-space planner for human-like straight locomotion that target application
of in rehabilitation robotics and computational neuroscience. The proposed
architecture is based on the potential energy model and employs locomotor
strategies from human data as a reference for human behaviour. The model
generates Centre of Mass (CoM) trajectories, foot swing trajectories and the
Base of Support (BoS) over time. The data show that the proposed architecture
can generate behaviour in line with human walking strategies for both the CoM
and the foot swing. Despite the CoM vertical trajectory being not as smooth as
a human trajectory, yet the proposed model significantly reduces the error in
the estimation of the CoM vertical trajectory compared to the inverted pendulum
models. The proposed model is also able to asses the stability based on the
body kinematics embedding in currently used in the clinical practice. However,
the model also implies a shift in the interpretation of the spatiotemporal
parameters of the gait, which are now determined by the conditions for the
equilibrium and not \textit{vice versa}. In other words, locomotion is a
dynamic reaching where the motor primitives are also determined by gravity.
