A Novel Velocity-Based Control in a Sensor Space for Parallel Manipulators.

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.

Design of a Low-Power Embedded System Based on a SoC-FPGA and the Honeybee Search Algorithm for Real-Time Video Tracking.

Video tracking involves detecting previously designated objects of interest within a sequence of image frames. It can be applied in robotics, unmanned vehicles, and automation, among other fields of interest. Video tracking is still regarded as an open problem due to a number of obstacles that still need to be overcome, including the need for high precision and real-time results, as well as portability and low-power demands. This work presents the design, implementation and assessment of a low-power embedded system based on an SoC-FPGA platform and the honeybee search algorithm (HSA) for real-time video tracking. HSA is a meta-heuristic that combines evolutionary computing and swarm intelligence techniques. Our findings demonstrated that the combination of SoC-FPGA and HSA reduced the consumption of computational resources, allowing real-time multiprocessing without a reduction in precision, and with the advantage of lower power consumption, which enabled portability. A starker difference was observed when measuring the power consumption. The proposed SoC-FPGA system consumed about 5 Watts, whereas the CPU-GPU system required more than 200 Watts. A general recommendation obtained from this research is to use SoC-FPGA over CPU-GPU to work with meta-heuristics in computer vision applications when an embedded solution is required.

Impedance control in a wave-based teleoperator for rehabilitation motor therapies assisted by robots.

This paper presents an improved wave-based bilateral teleoperation scheme for rehabilitation therapies assisted by robot manipulators. The main feature of this bilateral teleoperator is that both robot manipulators, master and slave, are controlled by impedance. Thus, a pair of motion-based adaptive impedance controllers are integrated into a wave-based configuration, in order to guarantee a stable human-robot interaction and to compensate the position drift, characteristic of the available schemes of bilateral teleoperation. Moreover, the teleoperator stability, in the presence of time delays in the communication channel, is guaranteed because the wave-variable approach is included to encode the force and velocity signals. It should be noted that the proposed structure enables the implementation of several teleoperator schemes, from passive therapies, without the intervention of a human operator on the master side, to fully active therapies where both manipulators interact with humans in a stable manner. The suitable performance of the proposed teleoperator is verified through some results obtained from the simulation of the passive and active-constrained modes, by considering typical tasks in motor-therapy rehabilitation, where an improved behavior is observed when compared to implementations of the classical wave-based approach.

Aplicación de sensores múltiples para el posicionamiento tridimensional de robots usando visión / Application of multiple sensors for three-dimensional robot positioning using vision

El presente artículo expone aspectos de una metodología para el posicionamiento tridimensional de una herramienta manipulada por un robot industrial usando una técnica basada en el uso de visión artificial conocida como manipulación de espacio de cámara. Se describe el uso de múltiples sensores para realizar la maniobra de posicionamiento que ofrece la ventaja de aumentar la precisión del sistema y al mismo tiempo, brindar una alternativa que permita incrementar el volumen de trabajo en el que el robot es capaz de realizar la maniobra. La metodología que se propone se ha probado experimentalmente usando un robot industrial Fanic ArcMate 100i, con equipo de visión convencional y un sistema de luz láser estructural que facilita la tarea de análisis de las imágenes de las superficies arbitrarias sobre las que se realiza la tarea