Alejandro González

@article{Loredo2022,

title = {A Novel Velocity-Based Control in a Sensor Space for Parallel Manipulators},

author = {Antonio Loredo and Mauro Maya and Alejandro González and Antonio Cardenas and Emilio Gonzalez-Galvan and Davide Piovesan},

url = {https://doi.org/10.3390/s22197323},

doi = {10.3390/s22197323},

issn = {1424-8220},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

journal = {Sensors},

volume = {22},

number = {19},

pages = {7323},

abstract = {It is a challenging task to track objects moving along an unknown trajectory. Conventional model-based controllers require detailed knowledge of a robot's kinematics and the target's trajectory. Tracking precision heavily relies on kinematics to infer the trajectory. Control implementation in parallel robots is especially difficult due to their complex kinematics. Vision-based controllers are robust to uncertainties of a robot's kinematic model since they can correct end-point trajectories as error estimates become available. Robustness is guaranteed by taking the vision sensor's model into account when designing the control law. All camera space manipulation (CSM) models in the literature are position-based, where the mapping between the end effector position in the Cartesian space and sensor space is established. Such models are not appropriate for tracking moving targets because the relationship between the target and the end effector is a fixed point. The present work builds upon the literature by presenting a novel CSM velocity-based control that establishes a relationship between a movable trajectory and the end effector position. Its efficacy is shown on a Delta-type parallel robot. Three types of experiments were performed: (a) static tracking (average error of 1.09 mm); (b) constant speed linear trajectory tracking-speeds of 7, 9.5, and 12 cm/s-(tracking errors of 8.89, 11.76, and 18.65 mm, respectively); (c) freehand trajectory tracking (max tracking errors of 11.79 mm during motion and max static positioning errors of 1.44 mm once the object stopped). The resulting control cycle time was 48 ms. The results obtained show a reduction in the tracking errors for this robot with respect to previously published control strategies.},

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pubstate = {published},

tppubtype = {article}

}

@article{Cardenas2021,

title = {Vision-Based Control of a Mobile Manipulator With an Adaptable-Passive Suspension for Unstructured Environments},

author = {Antonio Cardenas and Osmar Quiroz and Ricardo Hernández and Hugo I. Medellin-Castillo and Alejandro González and Mauro Maya and Davide Piovesan},

url = {https://asmedigitalcollection.asme.org/mechanismsrobotics/article/13/5/050908/1110842/Vision-Based-Control-of-a-Mobile-Manipulator-With},

doi = {10.1115/1.4051437},

issn = {1942-4302},

year  = {2021},

date = {2021-01-01},

journal = {Journal of Mechanisms and Robotics},

volume = {13},

issue = {5},

pages = {050908.1-050908.12},

abstract = {The kinematic design, development, and navigation control of a new autonomous mobile manipulator for unstructured terrain is presented in this work. An innovative suspension system is designed based on the kinematic synthesis of an adaptable, passive mechanism. This novel suspension can compensate for irregularities in the terrain by using two pairs of bogies joined by a crank-slider mechanism and facilitates the control of the robotic platform using video cameras. The mobile robot is also equipped with a robotic manipulator, of which a synthesis, simulation, and experimental validation are presented. Additionally, manipulation is accomplished during motion on rough terrain. The proposed mobile robot has been fabricated using additive manufacturing (AM) techniques. A vision-based control approach, from here on named mobile linear-camera space manipulation (MLCSM), for mobile manipulators has been synthesized and implemented to conduct experimental tests. This mobile manipulator has been designed to traverse uneven terrain so that the loading platform is kept close to horizontal while crossing obstacles up to one-third of the size of its wheels. This feature allows for the onboard cameras to stay oriented toward the target; it also allows for any device mounted on the payload platform to remain nearly horizontal during the task. The developed control approach allows us to estimate the position and orientation of the manipulator’s end effector and update its trajectory along the path toward the target. The experiments show a final precision for engagement of a pallet within +/−2.5 mm in position and +/−2 deg in orientation},

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pubstate = {published},

tppubtype = {article}

}

@article{Coronado2021,

title = {Self-Tuning Extended Kalman Filter Parameters to Identify Ankle's Third-Order Mechanics},

author = {E. Coronado and Alejandro González and A. Cárdenas and Mauro Maya and Enrico Chiovetto and Davide Piovesan},

url = {https://asmedigitalcollection.asme.org/biomechanical/article/doi/10.1115/1.4048042/1086083/SelfTuning-Extended-Kalman-Filter-Parameters-to},

doi = {10.1115/1.4048042},

issn = {0148-0731},

year  = {2021},

date = {2021-01-01},

journal = {Journal of Biomechanical Engineering},

volume = {143},

issue = {1},

pages = {1-8},

abstract = {The estimation of human ankle's mechanical impedance is an important tool for modeling human balance. This work presents the implementation of a parameter-estimation approach based on a state-augmented extended Kalman filter (AEKF) to infer the ankle's mechanical impedance during quiet standing. However, the AEKF filter is sensitive to the initialization of the noise covariance matrices. In order to avoid a time-consuming trial-and-error method and to obtain a better estimation performance, a genetic algorithm (GA) is proposed to best tune the measurement noise (Rk) and process noise covariances (Q) of the extended Kalman filter (EKF). Results using simulated data show the efficacy of the proposed algorithm for parameter-estimation of a third-order biomechanical model. Experimental validation of these results is also presented. They suggest that age is an influencing factor in the human balance.},

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pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {An extended statically equivalent serial chain—Identification of whole body center of mass with dynamic motion},

author = {Alejandro González and Philippe Fraisse and Mitsuhiro Hayashibe},

url = {https://linkinghub.elsevier.com/retrieve/pii/S0966636220306482},

doi = {10.1016/j.gaitpost.2020.11.021},

issn = {09666362},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {Gait & Posture},

volume = {84},

pages = {45-51},

abstract = {Background:

Tracking the whole body center of mass (CoM) trajectory of balance-impaired individuals with a personalized model is useful in the development of customized fall prevention strategies. A personalized CoM estimate can be obtained using the statically equivalent serial chain (SESC) method, but the subject has to perform an identification procedure to determine the set of subject-specific SESC parameters. During this identification, the subject must hold a series of static poses, some of which are unsuitable for balanced-impaired individuals.



Research question:

Can non-static poses be used to replace the static poses during SESC parameter identification?



Methods:

A new method that extends the range of postures used to determine SESC parameters is presented. It takes advantage of CoM dynamics and can be executed by predominantly using dynamic motions with a few static frames. Furthermore, it is implemented using a Kalman filter to allow automatic switching between the dynamic and static models. The proposed method was tested with motion data obtained from seven healthy adults using a Vicon motion capture system and an AMTI force platform.



Results:

We found that dynamic motions could be used to estimate the SESC parameter and even reproduce ground reaction forces; however a small number of static poses are still required to determine the subject’s CoM position. The SESC-based CoM estimate obtained with this new approach was similar to that obtained using conventional full-static identification, except that the subject did not have to assume and maintain static poses.



Significance:

Our proposed extension of the conventional SESC method would facilitate its application in the field of neuro-rehabilitation, especially in patients who need balance training. This personalized CoM method could be applicable for patients who are not able to maintain a static posture. In addition, this method helps minimize the total identification time by increasing the number of usable recorded frames.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}