Juan Daniel Ramirez-Zamora

There exist several methods aimed at human–robot physical interaction (HRpI) to provide physical therapy in patients. The use of haptics has become an option to display forces along a given path so as to it guides the physiotherapist protocol. Critical in this regard is the motion control for haptic guidance to convey the specifications of the clinical protocol. Given the inherent patient variability, a conclusive demand of these HRpI methods is the need to modify online its response with neither rejecting nor neglecting interaction forces but to process them as patient interaction. In this paper, considering the nonlinear dynamics of the robot interacting bilaterally with a patient, we propose a novel adaptive control to guarantee stable haptic guidance by processing the causality of patient interaction forces, despite unknown robot dynamics and uncertainties. The controller implements radial basis neural network with daughter RASP1 wavelets activation function to identify the coupled interaction dynamics. For an efficient online implementation, an output infinite impulse response filter prunes negligible signals and nodes to deal with overparametrization. This contributes to adapt online the feedback gains of a globally stable discrete PID regulator to yield stiffness control, so the user is guided within a perceptual force field. Effectiveness of the proposed method is verified in real-time bimanual human-in-the-loop experiments.

Haptic exploration for high precision applications such as surgical training stations, represent a challenge in kinesthetic force feedback methods with deformable virtual objects. In this contribution, a methodology to compute the contact forces for haptic interfaces with high performance, is presented to define the force in the human interaction with the virtual environment. To this end, the method is based on the orthogonal decomposition principle applied to robot force controllers, in this case, to generate deformable viscoelastic and tangent friction properties on the virtual surface, during haptic exploration. The dynamics of the normal plane is defined by a spring-damper system, and the dynamics of the tangent plane from a viscous-Coulomb friction model. The experimental platform corresponds to a haptic device based on the impedance principle (compute of force as a function of the movement) of 6 degrees of freedom, 3 degrees of freedom fully actuated for position and force control. The interaction task consists of two phases: i) numerical validation in Matlab, the forward and inverse kinematics of the position and veocity of the haptic device are used., and ii) validation in a virtual environment programmed in CHAI 3D and Visual C++, described by a virtual sphere with deformable and tangent dynamics.

La cinemática de posición y diferencial, para un dispositivo háptico, representan el modelo matemático que describe el comportamiento y la evolución de su geometría espacial. Las contribuciones en un sistema de Interacción Física Humano-Robot son: i) planificación del movimiento cartesiano operativo y verificación del desempeño en las tareas de la guía táctil pasiva, ii) relación par / fuerza a través de la matriz Jacobiana analítica con propósitos en exploración háptica activa, iii) Análisis de manipulación cinemática en tiempo real y trayectorias de planificación. En este trabajo se obtiene el modelo cinemático de posición y diferencial, así como simulaciones y validaciones experimentales, para un dispositivo háptico CyberForce en su cadena cinemática de posición.

The position and differential kinematics, for a haptic device, represent the mathematical model that describes the behavior and evolution of its spatial geometry. Contributions in a Human-Robot Physical Interaction system, are: i) operational cartesian motion planning and verification of performance on tasks of passive haptic guidance, ii) torque / force relationship through the analytical Jacobian matrix with purposes in active haptic exploration, iii) the kinematic manipulability analysis in real-time and re-planning paths. In this paper obtaining the position and differential kinematics as well as simulation and experimental validations, for a CyberForce haptic device in its position kinematics chain.

This paper shows the experimental validation of the forward and inverse kinematic model (position and velocity), of the CyberForce haptic device (CHD). For trajectory tracking is used a passive control technique in operational coordinates (cartesian workspace) and its experimental results in the joint-space. The contribution in passive haptic guidance, is on virtual maze navigation with purposes of diagnosis and rehabilitation of upper limb, and training only as a proof platform without any patients, to this end, for the motion planning is used a time base generator for tracking in finite time.

The human-robot physical interaction systems (HRpI), are platforms designed for the transmission of knowledge, from contact between a human kinesthetic, and a robotic device with inertial dynamic and tribological low. The dynamic of contact for the robotic system is modified to the inertial, gravitational forces and tribology (friction and mechanical vibrations); that represent uncertainty in the cooperative scheme the human operator responds differently in different experimental events. The robot control strategies are remarkably insufficient stabilization classical systems (conventional PID control), or nonlinear robust controls where no significant changes in the control gains based on the dynamic of interaction. In this research, the design and implementation of a Wavenet control (Multiresolution PID control based on Wavelet neural networks of second generation as a identification scheme) and first time is evaluated in a device with high technological performance Cyberforce) designed for positioning an exoskeleton CyberGrasp with the human operator in the loop.