Neurophysiological models of gaze control in Humanoid Robotics

This work present a robotic implementation of a neurophysiological model of rapid orienting gaze shifts in humans, with the final goal of model parameters validation and tuning. The quantitative assessment of robot performance confirmed a good ability to foveate the target with low residual errors around the desired target position. Furthermore, the ability to maintain the desired position was good and the gaze fixation after the saccadic movement was executed with only few oscillations of the head and eye. This is because the model required a very high dynamic. 9.1. Robotic point of view The head and eye residual oscillations increase linearly with increasing amplitude. In Fig. 16 is evident that the residual gaze oscillation is less than head. This is explained with the compensation introduced by the eye oscillations which compensate the gaze which becomes more stable. We explain these findings by observing that the accelerations required to execute (or stopand-invert) the movement are very high especially for the eye movement. Even if the robotic head was designed to match the human performances (in terms of angle and velocities) in its present configuration it is still not capable produce such accelerations. This is particularly evident for the movement of the eye because the motor has to invert its rotation when the fixation point is first achieved. With respect to the timing of the movement it has been found that the results of the experiments are in close accordance to the data available on humans (Goossens and Van Opstal, 1997). The same conclusion may be drawn for the shapes of the coordinated movement that can be directly compared to the typical examples reported in Fig. 14. Figure 16, 17 show that the model is capable of providing inadequate control of the redundant platform. The system response is very fast, due to the robotic head platform design. TGst time take into account the problem of eye-head coordination and the very high acceleration. The head is voluntarily delayed less than 30 millisecond after eye movement, according to human physiology, by means of Ph block (Goossens and Van Opstal ,1997). 9.2. Neurophysiological point of view A typical robotic eye-head movement is shows in Fig. 14

Insect inspired visual motion sensing and flying robots

International audienceFlying insects excellently master visual motion sensing techniques. They use dedicated motion processing circuits at a low energy and computational costs. Thanks to observations obtained on insect visual guidance, we developed visual motion sensors and bio-inspired autopilots dedicated to flying robots. Optic flow-based visuomotor control systems have been implemented on an increasingly large number of sighted autonomous robots. In this chapter, we present how we designed and constructed local motion sensors and how we implemented bio-inspired visual guidance scheme on-board several micro-aerial vehicles. An hyperacurate sensor in which retinal micro-scanning movements are performed via a small piezo-bender actuator was mounted onto a miniature aerial robot. The OSCAR II robot is able to track a moving target accurately by exploiting the microscan-ning movement imposed to its eye's retina. We also present two interdependent control schemes driving the eye in robot angular position and the robot's body angular position with respect to a visual target but without any knowledge of the robot's orientation in the global frame. This "steering-by-gazing" control strategy, which is implemented on this lightweight (100 g) miniature sighted aerial robot, demonstrates the effectiveness of this biomimetic visual/inertial heading control strategy

Steering by Gazing: An Efficient Biomimetic Control Strategy for Visually-guided Micro-Air Vehicles

International audienceOSCAR 2 is a twin-engine aerial demonstrator equipped with a monocular visual system, which manages to keep its gaze and its heading steadily fixed on a target (a dark edge or a bar) in spite of the severe random perturbations applied to its body via a ducted fan. The tethered robot stabilizes its gaze on the basis of two Oculomotor Reflexes (ORs) inspired by studies on animals: - a Visual Fixation Reflex (VFR) - a Vestibulo-ocular Reflex (VOR) One of the key features of this robot is the fact that the eye is decoupled mechanically from the body about the vertical (yaw) axis. To meet the conflicting requirements of high accuracy and fast ocular responses, a miniature (2.4-gram) Voice Coil Motor (VCM) was used, which enables the eye to make a change of orientation within an unusually short rise time (19ms). The robot, which was equipped with a high bandwidth (7Hz) "Vestibulo-Ocular Reflex (VOR)" based on an inertial micro-rate gyro, is capable of accurate visual fixation as long as there is light. The robot is also able to pursue a moving target in the presence of erratic gusts of wind. Here we present the two interdependent control schemes driving the eye in the robot and the robot in space without any knowledge of the robot's angular position. This "steering by gazing" control strategy implemented on this lightweight (100-gram) miniature aerial robot demonstrates the effectiveness of this biomimetic visual/inertial heading control strategy

Visual attention and perception in scene understanding for social robotics

Ph.DDOCTOR OF PHILOSOPH

Towards adaptive and autonomous humanoid robots: from vision to actions

Although robotics research has seen advances over the last decades robots are still not in widespread use outside industrial applications. Yet a range of proposed scenarios have robots working together, helping and coexisting with humans in daily life. In all these a clear need to deal with a more unstructured, changing environment arises. I herein present a system that aims to overcome the limitations of highly complex robotic systems, in terms of autonomy and adaptation. The main focus of research is to investigate the use of visual feedback for improving reaching and grasping capabilities of complex robots. To facilitate this a combined integration of computer vision and machine learning techniques is employed. From a robot vision point of view the combination of domain knowledge from both imaging processing and machine learning techniques, can expand the capabilities of robots. I present a novel framework called Cartesian Genetic Programming for Image Processing (CGP-IP). CGP-IP can be trained to detect objects in the incoming camera streams and successfully demonstrated on many different problem domains. The approach requires only a few training images (it was tested with 5 to 10 images per experiment) is fast, scalable and robust yet requires very small training sets. Additionally, it can generate human readable programs that can be further customized and tuned. While CGP-IP is a supervised-learning technique, I show an integration on the iCub, that allows for the autonomous learning of object detection and identification. Finally this dissertation includes two proof-of-concepts that integrate the motion and action sides. First, reactive reaching and grasping is shown. It allows the robot to avoid obstacles detected in the visual stream, while reaching for the intended target object. Furthermore the integration enables us to use the robot in non-static environments, i.e. the reaching is adapted on-the- fly from the visual feedback received, e.g. when an obstacle is moved into the trajectory. The second integration highlights the capabilities of these frameworks, by improving the visual detection by performing object manipulation actions

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

Human-Robot Collaborations in Industrial Automation

Technology is changing the manufacturing world. For example, sensors are being used to track inventories from the manufacturing floor up to a retail shelf or a customer’s door. These types of interconnected systems have been called the fourth industrial revolution, also known as Industry 4.0, and are projected to lower manufacturing costs. As industry moves toward these integrated technologies and lower costs, engineers will need to connect these systems via the Internet of Things (IoT). These engineers will also need to design how these connected systems interact with humans. The focus of this Special Issue is the smart sensors used in these human–robot collaborations