Parameter identification and modeling of contact properties for robotic applications

Resumen

The sense of touch is especially important in task performance in unstructured environments. Many of the tasks we perform normally would be problematic, if not impossible, without sensory information of this type. Daily tasks that we take for granted, such as chewing or walking require the use of tactile information (pressure, exerted force, etc.) to be done. Thus, it is logical to think that in order to build robots capable of performing tasks in unstructured environments, it is necessary to provide them with the same information. A research area that would benefit from the inclusion of tactile information, and one that is of particular interest to robotics, is biomimetic locomotion. Improving biomimetic locomotion can impact fields such as service robotics, rehabilitation robotics, and search and rescue robots. For this reason, we will focus on biomimetic locomotion, but we will keep in other applications that can use haptic perception. Animals change their apparent leg stiffness when changing from a rigid surface to a softer one. This change is done because animals and humans maintain the same center of mass trajectory in different surfaces; thus, a change on the apparent stiffness must occur. The realization of this change requires information on the contact properties of the environment. How to extract this information is a question that still needs much research. Because of this, we have done an experimental study that compares the performance of different system identification techniques when they are applied to contact modeling. During the evaluation of the results it was found that the recursive least squares method has the best performance for haptic applications. Based on the results of this study we have selected the recursive least squares method and the spring dashpot model. With this design parameters, we devised an algorithm to be used in a robotic leg. The algorithm was implemented on a 3-degree-of-freedom (DoF) underactuated leg and then it was tested using four different terrains. The results show that the algorithm was capable of differentiating between terrains according to their stiffness and that the convergence time was under the average time a human runner is in contact with the ground. Nevertheless, the algorithm was not able to differentiate the damping coefficient in granular media. This result is to be expected because granular media are extremely complex and can exhibit highly nonlinear behavior. To solve this problem, we proposed a new contact model based on the conservation of momentum and the similarities of granular media with liquids. The model was tested under different experimental conditions, varying the dynamic and geometric properties of the contact with satisfactory results. However, it was found that changing the geometric properties has an impact in the obtained parameters, because it changes the dynamics of the interaction between the actuator and the surface. A solution for this problem might be to use pressure instead of exerted force as an input to the model It is important to note that the results of this work have been published in five articles in Journal Citation Report indexed journals and 13 publication in International Scientific Index proceedings. Furthermore, to continue with the research of this thesis a possible line is the reformulation of the proposed model to use pressure instead of force as an input, and to implement the proposed identification algorithm in an exoskeleton or a walking robot to select the appropriate impedance of the legs at each step.