Loulin Huang

Robot-Assisted Therapy for Learning and Social Interaction of Children with Autism Spectrum Disorder

This paper puts forward the potential for designing a parrot-inspired robot and an indirect teaching technique, the adapted model-rival method (AMRM), to help improve learning and social interaction abilities of children with autism spectrum disorder. The AMRM was formulated by adapting two popular conventional approaches, namely, model-rival method and label-training procedure. In our validation trials, we used a semi-autonomous parrot-inspired robot, called KiliRo, to simulate a set of autonomous behaviors. A proposed robot-assisted therapy using AMRM was pilot tested with nine children with autism spectrum disorder for five consecutive days in a clinical setting. We analyzed the facial expressions of children when they interacted with KiliRo using an automated emotion recognition and classification system, Oxford emotion API (Application Programming Interface). Results provided some indication that the children with autism spectrum disorder appeared attracted and happy to interact with the parrot-inspired robot. Short qualitative interviews with the children’s parents, the pediatrician, and the child psychologist who participated in this pilot study, also acknowledged that the proposed parrot-inspired robot and the AMRM may have some merit in aiding in improving learning and social interaction abilities of children with autism spectrum disorder.

An approach for robust control of a twin-rotor multiple input multiple output system

The twin-rotor multiple input multiple output system (TRMS) developed by Feedback Instruments Limited [1] consists of two axes corresponding to yaw and pitch angles commonly found in an aerial vehicle. The system can be used as a generic platform for testing MIMO controllers. This paper presents a robust control approach to stabilize the TRMS in a desired posture based on the dynamic model provided by the manufacturer. It is well known that the model is too complex in structure to be used for controller design. In the robust control approach proposed in the paper, it is approximated by a simplified model and the approximation error is compensated by a sliding mode control. In addition, the effect of the quality of the system state feedback on the controllers performance is discussed and a way to improve it is implemented. Experimental results are provided to verify the effectiveness of the approach.

Experimental study on sensor fusion to improve real time indoor localization of a mobile robot

Reliable indoor navigation of mobile robots has been a popular research topic in recent years. GPS systems used for outdoor mobile robot navigation cannot be used indoor (warehouse, hospital or other buildings) because GPS require an unobstructed view of the sky. Therefore a specially designed indoor localisation system for mobile robot is needed. This paper aims to develop a reliable position and heading angle estimator for real time indoor localization of a mobile robot. The proposed technique is achieved by fusing three different sensor modules based on infrared sensing, calibrated odometry and gyroscopes and applying the real time filtering technique Kalman filter. It can provide filtered and reliable information of a mobile robots current location and orientation relative to its environment. Extensive experimental results are provided to demonstrate its improvement over conventional dead reckoning method.

An approach for coverage path planning for UAVs

In this paper, an offline flight planner that computes an efficient coverage trajectory for a quad-rotors UAV is presented. The planner consists of three steps: mission definition, automatic path planning and trajectory generation. The proposed planner, as a useful tool, allows an UAV operator to easily define and generate a coverage trajectory for any specific task. The resultant trajectory can be dispatched to a quad-rotors with trajectory tracking controller for the missions that require a complete area coverage.

Effects of Adapted Model-Rival Method and parrot-inspired robot in improving learning and social interaction among children with autism

Educating children with autism is becoming a highly challenging task due to the nature of the disorder and limited interest of these children in interacting with people. Nevertheless, it is observed that most of the children with autism are good observers. This paper put forward and evaluates a novel teaching technique, Adapted Model-Rival Method (AMRM and a parrot-inspired robot for children with autism to help improve learning and social interaction abilities through qualitative and quantitative analysis. We begin by discussing various medications, therapy, and teaching methods used in treating autism and emphasizing the importance and benefits of implementing an indirect teaching method. We then present our novel indirect teaching method, AMRM and the benefits of using a parrot-inspired robot as an intervention tool. Finally, we discuss the results of our study conducted for five consecutive days with nine participants.

Experimental evaluation of parrot-inspired robot and adapted model-rival method for teaching children with autism

The use of biologically inspired robots in therapeutic settings could offer new possibilities for improving learning and social interaction abilities of children with autism. This paper introduces a novel teaching method, Adapted Model-Rival Method, together with a parrot-inspired robot (KiliRo) to help children with autism in learning and social interaction. The proposed indirect teaching method and the parrot-like robot morphology were tested with 9 children identified with autism. The test was conducted for 5 consecutive days for the same participants at the same place. In this study, the emotions of participating children during the experiment were analyzed using an automated emotion recognition and classification system, Oxford emotion API through facial images. Totally, 580 pictures were taken to obtain 2360 individual facial emotion values for evaluation. The results show that the happiness of subjects improved from day 1 through day 5 of the study through interacting with the robot. It is also reported that the participating children were attracted to the robot when it was exhibiting its learning abilities. Our study also indicates that the children with autism are not afraid of parrot-like robots and are happy to interact with it.

Counting insects in flight using image processing techniques

A method to monitor New Zealands native bees using image processing technology is presented. Since most species are solitary ground nesting bees the number of active nests within an area can give a good estimate of the population of a community. The number of native bees in flight around plants can also provide valuable information about the overall health of a community and help to quantify their value in the ecosystem as keystone pollinators. On this basis, images of insects in flight have been collected across one season and the results compared with previous results of active nest counts. Open source software FIJI was used to pre-process and classify images. Accuracies were verified using data mining software WEKA. Performance evaluations showed the fast random forest classifier consistently returned fast, accurate results. Fine differences in images were discriminated that were otherwise impossible to identify with the naked eye and even when training data were unevenly distributed the classifier returned accuracies above 98%. The results are promising and while there are few alternatives to traditional methods, image processing for ecology can provide cost effective, standardized tools to help monitor the population and diversity of native bees in New Zealand.

An image based approach to monitor New Zealand native bees

A cost effective image based approach is proposed for monitoring New Zealand native bees, they are difficult to study, and require expert taxonomic identification due to minimal morphological differences between species. They have seasonal life-cycles which require long-term studies. Rather than identifying individual bees directly, as is done in most traditional ecological methods, the ground nests are identified and counted. The number of active nests can then be used to estimate the population of bees. This is possible because the number of bees in each nest is constant for most solitary mining species. A thorough field study has been conducted and a range of rich image data has been collected. Open source programs, Fiji and WEKA were used to implement computer vision techniques for pre-processing images, classification, accuracy verification and comparisons between random forest and support vector machine classifiers. The randon forest classifier in Fiji provided fast effective results classifying nests which were otherwise difficult to identify with the naked eye. This method is shown to be robust and simple with a potential to provide ecologists with repeatable and reliable estimations of the population status of New Zealand native bees.

Sociopsychological and physiological effects of a robot-assisted therapy for children with autism:

This article reports our findings from a robot-assisted therapeutic study conducted over 49 days to investigate the sociopsychological and physiological effects in children with autism spectrum disorder using a parrot-inspired robot, KiliRo, that we developed to help in therapeutic settings. We investigated the frequency of participants’ interactions among each other and assessed any changes in interaction using social network analysis. Interactions were assessed through manual observation before and after exposure to the robot. Urinary and salivary tests were performed to obtain protein and α-amylase levels, respectively, to report the physiological changes in participating children with autism spectrum disorder before and after interacting with the robot. This is a pioneering human–robot interaction study to investigate changes in stress levels using salivary samples. Systolic and diastolic blood pressure, heart rate, and arterial oxygen saturation level in blood were also monitored to investigate the physiological changes in participating children before, during, and after interacting with our parrot-inspired robot, KiliRo. The results show that the robot can help increase social interaction among children with autism spectrum disorder and assist in learning tasks. Furthermore, the clinical biochemistry test report using urinary and salivary samples indicates that the stress levels of children with autism reduced notably after interacting with the robot. Nevertheless, blood pressure, heart rate, and oxygen levels in blood did not show positive change in all participants.

Modelling and control of quadrotor maneuvers with variations of center of gravitry (COG)

In this paper, the effects of variations of the center of gravity (COG) on the quadrotor maneuvers is studied in terms of dynamic modeling and control. The quadrotors six degree freedom dynamic model is employed while the variation of the COG is treated as a motion tuner. As a result, a generalized dynamic model with extra motions is established. This model is simulated with the software packages MATLAB/ SIMULINK. To verify the model, some validation points are used to check the flight maneuver. Finally, the control of a reciprocating maneuver is designed by 2nd order sliding mode controller.