This work proposes the implementation and validation of a new sensor fusion strategy based on force sensors and LRF (Laser Range Finder) to control a robotic walker. This approach combines user information about forearm reaction forces and gait kinematics from the legs scanning localization, to develop a more natural, safer and adaptable human-walker interaction. The work was carried out in four phases. First, a robotic walker platform was developed and the sensor subsystems were integrated. Second, a sensor fusion strategy to obtain the control parameters are defined. Third, the control strategy is presented. Finally, an experimental study to evaluate the sensor architecture and control was developed. One of the advantages of the humanwalker interaction here proposed is the computational efficiency. The sensor processing algorithms and the control strategy are executed in real-time, showing stable performance with human speed changes.