This thesis presents an effective alternative to the traditionalapproach to robotic manipulation. In our approach, manipulation ismainly guided by tactile feedback as opposed to vision. Themotivation comes from the fact that manipulating an object impliescoming in contact with it, consequently, directly sensing physicalcontact seems more important than vision to control theinteraction of the object and the robot. In this work, thetraditional approach of a highly precise arm and vision systemcontrolled by a model-based architecture is replaced by one thatuses a low mechanical impedance arm with dense tactile sensing andexploration capabilities run by a behavior-based architecture.The robot OBRERO has been built to implement this approach. Newtactile sensing technology has been developed and mounted on therobot's hand. These sensors are biologically inspired and presentmore adequate features for manipulation than those of state of theart tactile sensors. The robot's limb was built with compliantactuators, which present low mechanical impedance, to make theinteraction between the robot and the environment safer than thatof a traditional high-stiffness arm. A new actuator was created tofit in the hand size constraints. The reduced precision ofOBRERO's limb is compensated by the capability of explorationgiven by the tactile sensors, actuators and the softwarearchitecture.The success of this approach is shown by picking up objects in anunmodelled environment. This task, simple for humans, has been achallenge for robots. The robot can deal with new, unmodelledobjects. OBRERO can come gently in contact, explore, lift, andplace the object in a different location. It can also detectslippage and external forces acting on an object while it is held.Each one of these steps are done by using tactile feedback. Thistask can be done with very light objects with no fixtures and onslippery surfaces.