Conventional assistive and rehabilitative robotic systems often overlook human biomechanics, particularly muscular forces, as they predominantly operate in joint or task space and focus on position and exchanged forces. Similarly, traditional manual rehabilitation techniques employed by physiotherapists struggle to obtain quantitative measurements and make precise modifications to key human variables, resulting in predominantly qualitative methods and outcomes. In response to these limitations, this article introduces an innovative assistive robot controller that operates in the muscular space, targeting specific muscles in the lower limb, and distinguishing itself from existing solutions that focus primarily on joint or task space. A key innovation of our approach is the real-time measurement of muscular forces during dynamic tasks, obtained from a calibrated musculoskeletal model. These measurements enable the establishment of a multistep closed-loop controller, with the outer loop precisely tracking the desired muscular forces. Implemented within a configurable viscous environment, the controller provides a natural response for the user. Experimental evaluations conducted using a parallel robot designed for rehabilitation demonstrate the controller’s efficacy. Incorporating the outer loop reduced the median relative error of the tracked muscular force by nearly 80% and decreased the variability of this error by over 85% compared to a pure viscous environment defined as the baseline. These findings highlight the potential applications of this control framework in areas, such as assistive robotics and precision rehabilitation. By achieving objective measurement and control, the system may enhance rehabilitation outcomes, offering tailored exercises that match the individual needs, capabilities, and engagement of each patient.

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.

As it is well known, robots are complex devices capable of performing very fast and precise movements. Developing robots and their controllers is a very challenge task due to the different technologies that are needed to be dealt with (access to peripherals, real-time operating systems, communications ...) and the amounts of programming work that is needed. Moreover, this work needs to be repeated in most cases when a new robot is developed. A new way is needed for developing the code implemented for controlling these robots that allows to reuse it in a safe way. In this paper, the Orocos (Open Robot Control Software) middleware has been chosen for the controller development. Orocos is a real-time middleware, focused on control systems, especially those related to robotics and automation. Its greatest advantage over the other solutions available is the capability to provide an off-the-shelf hard real-time operation. This is essential in most of the robotics applications, making this middleware in a very suitable piece of software. Since Orocos is a component-based middleware, several CBSD (component-based software development) techniques have been used to design and implement the control system. Thus, using a modular control structure, a number of advantages can be achieved such as code reusability, execution of the modules in a distributed way, ability to load or instantiate a module several times, easy following of flow execution and fewer programming errors. In addition, these components are configurable and reconfigurable in runtime.