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This article addresses a new way of generating compliant trajectories for control using movement primitives to allow physical human–robot interaction where parallel robots (PRs) are involved. PRs are suitable for tasks requiring precision and performance because of their robust behavior. However, two fundamental issues must be resolved to ensure safe operation: first, the force exerted on the human must be controlled and limited, and second, Type II singularities should be avoided to keep complete control of the robot. We offer a unified solution under the dynamic movement primitives (DMP) framework to tackle both tasks simultaneously. DMPs are used to get an abstract representation for movement generation and are involved in broad areas, such as imitation learning and movement recognition. For force control, we design an admittance controller intrinsically defined within the DMP structure, and subsequently, the Type II singularity evasion layer is added to the system. Both the admittance controller and the evader exploit the dynamic behavior of the DMP and its properties related to invariance and temporal coupling, and the whole system is deployed in a real PR meant for knee rehabilitation. The results show the capability of the system to perform safe rehabilitation exercises.

This article presents a new assembling for 2 degrees-of-freedom (DOFs) parallel robots for executing rapid pick-and-place operations with low energy consumption. A conventional design of 2-DOF parallel robots is based on five-bar mechanisms. Collisions between links are highly possible, restricting the end-effector workspace and/or increasing the trajectory time to avoid collisions. In this article, an alternative assembling for preventing collisions is presented. This novel assembling allows exploring the difference between the four five-bar mechanism configurations for the same position of the end-effector. Some of these configurations yield to lower time and/or lower energy consumption for the same motorization. First, a dynamic model of the robot has been developed using matlab® and simulink® and validated by comparison with the results obtained by adams® software. A robust cascade PD regulator for controlling joint coordinates has been tuned providing a high accurate end-effector positioning. Finally, simulation results of four configurations are presented for executing controlled maneuvers. The obtained results demonstrate that the conventional configuration is the worst one in terms of trajectory time or energy consumption and, conversely, the best one corresponds to an uncommonly used configuration. A workspace map where all configurations provide faster maneuvers has been obtained in terms of Jacobian matrix and mechanism elbows distance. The results presented here allow designing a rapid manipulator for pick-and-place operations.