Making Humanoid Robots More Acceptable Based on the Study of Robot Characters in Animation

Maleki, Fatemeh Shirmohammadzadeh; Farhoudi, Zeinab

doi:10.11591/ijra.v4i1.pp63-72

Cited by 3 publications

(1 citation statement)

References 5 publications

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“…On the other hand, motion-captured data from human performers are used to drive animated characters [9]. Obviously, this technique can be used to ease the generation of complicated movements as well as providing motion to the unutilized DOF and yielding natural movement for a humanoid robot.…”

Section: Introductionmentioning

confidence: 99%

Trajectory Planning and Walking Pattern Generation of Humanoid Robot Motion

Abdolshah

Tang

2014

IJRA

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Walking trajectory generation for a humanoid robot is a challenging control issue. In this paper, a walking cycle has been recognized considering human motion, and nine simple steps were distinguished in a full step of walking which form motion trajectory, and generates a simplified ZMP motion formulation. This system was used in humanoid robot simulation motion and is achievable easily in walking steps of robot. A minimum DOFs humanoid robot has been considered and geometrical relationships between the robot links were presented by the Denavit-Hartenberg method. The inverse kinematics equations have been solved regarding to extracted ZMP trajectory formula, and constraints in different steps. As a result; angular velocity, acceleration and power of motors were obtained using the relationships and Jacobin. At each step, extracted data were applied on simulated robot in Matlab, and Visual Nastran software. Zero moment point trajectory was evaluated in simulation environment.

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Section: Introductionmentioning

confidence: 99%

Trajectory Planning and Walking Pattern Generation of Humanoid Robot Motion

Abdolshah

Tang

2014

IJRA

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Distance Estimation based on Color-Block: A Simple Big-O Analysis

Rahmani¹,

Aprilianto²,

Ismanto³

et al. 2017

IJECE

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This paper explains how the process of reading the data object detection results with a certain color. In this case, the object is an orange tennis ball. We use a Pixy CMUcam5 connecting to the Arduino Nano with microcontroller ATmega328-based. Then through the USB port, data from Arduino nano re-read and displayed. It's to ensure weather an orange object is detected or not. By this process, it will be exactly known how many blocks object detected, including the X and Y coordinates of the object. Finally, it will be explained the complexity of the algorithms used in the process of reading the results of the detection orange object.

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Deep Learning-Based Cost-Effective and Responsive Robot for Autism Treatment

Singh

Raj

Kumar

et al. 2023

Drones

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Recent studies state that, for a person with autism spectrum disorder, learning and improvement is often seen in environments where technological tools are involved. A robot is an excellent tool to be used in therapy and teaching. It can transform teaching methods, not just in the classrooms but also in the in-house clinical practices. With the rapid advancement in deep learning techniques, robots became more capable of handling human behaviour. In this paper, we present a cost-efficient, socially designed robot called `Tinku’, developed to assist in teaching special needs children. `Tinku’ is low cost but is full of features and has the ability to produce human-like expressions. Its design is inspired by the widely accepted animated character `WALL-E’. Its capabilities include offline speech processing and computer vision—we used light object detection models, such as Yolo v3-tiny and single shot detector (SSD)—for obstacle avoidance, non-verbal communication, expressing emotions in an anthropomorphic way, etc. It uses an onboard deep learning technique to localize the objects in the scene and uses the information for semantic perception. We have developed several lessons for training using these features. A sample lesson about brushing is discussed to show the robot’s capabilities. Tinku is cute, and loaded with lots of features, and the management of all the processes is mind-blowing. It is developed in the supervision of clinical experts and its condition for application is taken care of. A small survey on the appearance is also discussed. More importantly, it is tested on small children for the acceptance of the technology and compatibility in terms of voice interaction. It helps autistic kids using state-of-the-art deep learning models. Autism Spectral disorders are being increasingly identified today’s world. The studies show that children are prone to interact with technology more comfortably than a with human instructor. To fulfil this demand, we presented a cost-effective solution in the form of a robot with some common lessons for the training of an autism-affected child.

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Making Humanoid Robots More Acceptable Based on the Study of Robot Characters in Animation

Cited by 3 publications

References 5 publications

Trajectory Planning and Walking Pattern Generation of Humanoid Robot Motion

Trajectory Planning and Walking Pattern Generation of Humanoid Robot Motion

Distance Estimation based on Color-Block: A Simple Big-O Analysis

Deep Learning-Based Cost-Effective and Responsive Robot for Autism Treatment

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