Symmetric Kullback-Leibler Metric Based Tracking Behaviors for Bioinspired Robotic Eyes

A symmetric Kullback-Leibler metric based tracking system, capable of tracking moving targets, is presented for a bionic spherical parallel mechanism to minimize a tracking error function to simulate smooth pursuit of human eyes. More specifically, we propose a real-time moving target tracking algorithm which utilizes spatial histograms taking into account symmetric Kullback-Leibler metric. In the proposed algorithm, the key spatial histograms are extracted and taken into particle filtering framework. Once the target is identified, an image-based control scheme is implemented to drive bionic spherical parallel mechanism such that the identified target is to be tracked at the center of the captured images. Meanwhile, the robot motion information is fed forward to develop an adaptive smooth tracking controller inspired by the Vestibuloocular Reflex mechanism. The proposed tracking system is designed to make the robot track dynamic objects when the robot travels through transmittable terrains, especially bumpy environment. To perform bumpy-resist capability under the condition of violent attitude variation when the robot works in the bumpy environment mentioned, experimental results demonstrate the effectiveness and robustness of our bioinspired tracking system using bionic spherical parallel mechanism inspired by head-eye coordination

Multimodal Sensory Integration for Perception and Action in High Functioning Children with Autism Spectrum Disorder

Movement disorders are the earliest observed features of autism spectrum disorder (ASD) present in infancy. Yet we do not understand the neural basis for impaired goal-directed movements in this population. To reach for an object, it is necessary to perceive the state of the arm and the object using multiple sensory modalities (e.g. vision, proprioception), to integrate those sensations into a motor plan, to execute the plan, and to update the plan based on the sensory consequences of action. In this dissertation, I present three studies in which I recorded hand paths of children with ASD and typically developing (TD) controls as they grasped the handle of a robotic device to control a cursor displayed on a video screen. First, participants performed discrete and continuous movements to capture targets. Cursor feedback was perturbed from the hand\u27s actual position to introduce visuo-spatial conflict between sensory and proprioceptive feedback. Relative to controls, children with ASD made greater errors, consistent with deficits of sensorimotor adaptive and strategic compensations. Second, participants performed a two-interval forced-choice discrimination task in which they perceived two movements of the visual cursor and/or the robot handle and then indicated which of the two movements was more curved. Children with ASD were impaired in their ability to discriminate movement kinematics when provided visual and proprioceptive information simultaneously, suggesting deficits of visuo-proprioceptive integration. Finally, participants made goal-directed reaching movements against a load while undergoing simultaneous functional magnetic resonance imaging (MRI). The load remained constant (predictable) within an initial block of trials and then varied randomly within four additional blocks. Children with ASD exhibited greater movement variability compared to controls during both constant and randomly-varying loads. MRI analysis identified marked differences in the extent and intensity of the neural activities supporting goal-directed reaching in children with ASD compared to TD children in both environmental conditions. Taken together, the three studies revealed deficits of multimodal sensory integration in children with ASD during perception and execution of goal-directed movements and ASD-related motor performance deficits have a telltale neural signature, as revealed by functional MR imaging

Precision Landing of a Quadrotor UAV on a Moving Target Using Low-Cost Sensors

With the use of unmanned aerial vehicles (UAVs) becoming more widespread, a need for precise autonomous landings has arisen. In the maritime setting, precise autonomous landings will help to provide a safe way to recover UAVs deployed from a ship. On land, numerous applications have been proposed for UAV and unmanned ground vehicle (UGV) teams where autonomous docking is required so that the UGVs can either recover or service a UAV in the field. Current state of the art approaches to solving the problem rely on expensive inertial measurement sensors and RTK or differential GPS systems. However, such a solution is not practical for many UAV systems. A framework to perform precision landings on a moving target using low-cost sensors is proposed in this thesis. Vision from a downward facing camera is used to track a target on the landing platform and generate high quality relative pose estimates. The landing procedure consists of three stages. First, a rendezvous stage commands the quadrotor on a path to intercept the target. A target acquisition stage then ensures that the quadrotor is tracking the landing target. Finally, visual measurements of the relative pose to the landing target are used in the target tracking stage where control and estimation are performed in a body-planar frame, without the use of GPS or magnetometer measurements. A comprehensive overview of the control and estimation required to realize the three stage landing approach is presented. Critical parts of the landing framework were implemented on an AscTec Pelican testbed. The AprilTag visual fiducial system is chosen for use as the landing target. Implementation details to improve the AprilTag detection pipeline are presented. Simulated and experimen- tal results validate key portions of the landing framework. The novel relative estimation scheme is evaluated in an indoor positioning system. Tracking and landing on a moving target is demonstrated in an indoor environment. Outdoor tests also validate the target tracking performance in the presence of wind

Precision Landing of a Quadrotor UAV on a Moving Target Using Low-Cost Sensors

With the use of unmanned aerial vehicles (UAVs) becoming more widespread, a need for precise autonomous landings has arisen. In the maritime setting, precise autonomous landings will help to provide a safe way to recover UAVs deployed from a ship. On land, numerous applications have been proposed for UAV and unmanned ground vehicle (UGV) teams where autonomous docking is required so that the UGVs can either recover or service a UAV in the field. Current state of the art approaches to solving the problem rely on expensive inertial measurement sensors and RTK or differential GPS systems. However, such a solution is not practical for many UAV systems. A framework to perform precision landings on a moving target using low-cost sensors is proposed in this thesis. Vision from a downward facing camera is used to track a target on the landing platform and generate high quality relative pose estimates. The landing procedure consists of three stages. First, a rendezvous stage commands the quadrotor on a path to intercept the target. A target acquisition stage then ensures that the quadrotor is tracking the landing target. Finally, visual measurements of the relative pose to the landing target are used in the target tracking stage where control and estimation are performed in a body-planar frame, without the use of GPS or magnetometer measurements. A comprehensive overview of the control and estimation required to realize the three stage landing approach is presented. Critical parts of the landing framework were implemented on an AscTec Pelican testbed. The AprilTag visual fiducial system is chosen for use as the landing target. Implementation details to improve the AprilTag detection pipeline are presented. Simulated and experimen- tal results validate key portions of the landing framework. The novel relative estimation scheme is evaluated in an indoor positioning system. Tracking and landing on a moving target is demonstrated in an indoor environment. Outdoor tests also validate the target tracking performance in the presence of wind

Real-Time Motion Compensation in Ship-to-Ship Load Handling

DoktorgradsavhandlingLike the automotive industry, the maritime industry is facing a higher demand for autonomous offshore operations. It is therefore in the author’s belief that the marine industry has to develop and implement new technology for both existing and new products to meet the increased autonomy demand. This thesis aims at presenting a unified understanding of the motions and the accompanying load handling issue in ship-to-ship operations. The ship-to-ship kinematics is modeled and a crane operator assistant is developed as a possible solution to increase the so-called weather window of ship-to-ship load transfers. The weather window is today determined by the significant wave height, and the current limitation of such operations is at 2.5m significant wave height. Proposing new methods capable of assisting the crane operator when transferring the load from one ship onto another is believed to further relax the weather window criteria, as well as increasing both the safety and efficiency of the operation itself. A novel ship-to-ship estimation algorithm using the well known Extended Kalman Filter (EKF) is developed and experimentally investigated in the Norwegian Motion Laboratory. In addition to the ship-to-ship observer, an observer for measuring the suspended load motions is developed. These estimators are used to form the novel crane operator assistant presented at the end of this thesis. The presented assistant consists of a wire-length assistant and an anti-swing assistant, which both aim at assisting the crane operator in ship-to-ship load transfers by adjusting the crane operator inputs slightly in real-time. The expected outcome is increased repeatability and efficiency, as well as reduced risk in general. The developed methods are described using a common and consistent mathematical notation for both the observers and the kinematic control systems. The appended papers at the end of this thesis have experimentally investigated and validated the proposed methods using several experiments which have been carried out in the Norwegian Motion Laborator

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

Robotics 2010

Without a doubt, robotics has made an incredible progress over the last decades. The vision of developing, designing and creating technical systems that help humans to achieve hard and complex tasks, has intelligently led to an incredible variety of solutions. There are barely technical fields that could exhibit more interdisciplinary interconnections like robotics. This fact is generated by highly complex challenges imposed by robotic systems, especially the requirement on intelligent and autonomous operation. This book tries to give an insight into the evolutionary process that takes place in robotics. It provides articles covering a wide range of this exciting area. The progress of technical challenges and concepts may illuminate the relationship between developments that seem to be completely different at first sight. The robotics remains an exciting scientific and engineering field. The community looks optimistically ahead and also looks forward for the future challenges and new development

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

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