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Meet Our Team
Embelias

Shubham Shukla

Dr. Shubham Shukla is an Associate Professor in KIET Group of Institutions and Assistant Research and Development Engineer, with an area of research in the field of Multi Robot Path Planning with Nature Inspired Algorithm.
He acted as the project guide in the development of Anushka Robot.

Atul Kumar

Mr. Atul Kumar is an expert in Power Electronics and Circuit Designing.
He is the hardware and electrical systems incharge of development team of Anushka Robot.

Piyush Khanna

Mr. Piyush Khanna is an experienced programmer with stack ranging from Software System Designing and Web Development to Machine Learning and IoT.
He is the incharge of software and electronic systems of development of Anushka Robot.

Govind Panwar

Mr. Govind Panwar is a software and DBA intern with Team Embelias.
He is responsible for the database retrieval and dataset collection for training custom data for the robot.

Harsh Jain

Mr. Harsh Jain is a hardware and Embedded Systems intern with Team Embelias.
He is responsible for R&D on circuitry and managing the supply of electronic components.

And together,
we

It's   all   possible

Face Recognition

Anushka excels in face recognition, employing cutting-edge computer vision to memorize faces in real-time with remarkable precision. This capability ensures accurate identification across diverse expressions and features, enabling personalized interactions in dynamic environments.
The implementation incorporates popular deep learning frameworks like TensorFlow and facial landmark detection algorithms to identify key points on a face, enhancing the efficiency and accuracy of face recognition.

Speech Recognition

With a support of over 40 Indian languages and major foreign languages including English, Spanish, Japanese etc, Anushka boasts a huge Natural Language Processing unit.

The NLP module in Anushka employs cutting-edge techniques, including sentiment analysis and contextual understanding, allowing it to grasp the emotional undertones of user queries. This not only enhances the quality of responses but also enables Anushka to tailor its communication style based on the user's emotional state.

Bot Operations Scheduling System

Bot Operations Scheduling System, shortened to BOSS, is the heart of Anushka robot's development. It is a dedicated Pseduo-OS specially designed to merge Linux's fast instruction control and Windows' huge support for python libraries. By acting as a hypervisor, it makes the robot extremely fast and responsive to all its sensing units.

It also acts as a messenger queue between all the modules of the robot and can actively command a module in case one of the vital modules fails.

Object identification and Tracking

Anushka has a dedicatedly developed computer vision program which enables it to approximate distance without a depth-sensing camera.

Whether it's following a person as they move around a room or tracking a specific object, Anushka's Object Tracking enhances its engagement capabilities. This feature is particularly valuable in environments where the robot needs to navigate and interact with its surroundings actively.

Cultural Integration with Vedic Principles

The entire system design and brain's response system of Anushka has been built after a thorough research on the Vedic views of human mind's architecture.

This integration aims to align the robot's decision-making processes with the holistic understanding of the mind presented in Vedic philosophy. Components such as 'Chitta', 'Manas', 'Ahankaram' and 'Buddhi' have been incorporated into the architecture of robot's Intelligence.

IoT and Automation

Anushka can integrate itself seamlessly into smart home, autonomously managing appliances like fans and bulbs based on predefined conditions.

Anushka also has the ability to completely automate the task of application writing and printing by performing print jobs from remote printers.
She can also make phone calls as well as send and recieve Whatsapp messages autonomously.

But,   How?


Team

Our beloved team worked tirelessly for 1.5 years to bring Anushka to life.


Make In India

Anushka, The Humanoid has been made to be represent Indian Robotics on international level.

Resources

*Note: All the media files are downloadable and open up in separate tab upon clicking. Thumbnails have been attached for video files.

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The Team Description Paper of Team Embelias for Robocup '24.

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Anushka in an interaction, showcasing its knowledge and creativity.

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Anushka showcasing its various gestures and sync of hands, neck and eye modules.

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Demonstration of Anushka's automatic tracking and following system.

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Anushka the robot showcasing the range of hand gestures she can make.

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Working of Jaw mechanism of the robot to synchronize with speech outputs.

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Starting gesture of the eye module of Anushka robot.

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Anushka the robot welcoming guests and strangers.

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The early stage of development, prototype of the Anushka robot.

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Anushka welcoming Sri Yogi Adityanath, Chief Minister of Uttar Pradesh, in the institute.

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Anushka talking to Dr. Atul Kothari, National Secretary, SSUN India.

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The family of Anushka, together in the Center of Robotics at KIET Group of Institutions.

Built As a
Make In India Initiative

About MakeInIndia

The Make in India initiative was launched by Prime Minister in September 2014 as part of a wider set of nation-building initiatives. Devised to transform India into a global design and manufacturing hub, Make in India was a timely response to a critical situation. By 2013, the much-hyped emerging markets bubble had burst, and India’s growth rate had fallen to its lowest level in a decade.

The promise of the BRICS Nations (Brazil, Russia, India, China and South Africa) had faded, and India was tagged as one of the so-called ‘Fragile Five’. Global investors debated whether the world’s largest democracy was a risk or an opportunity. India’s 1.2 billion citizens questioned whether India was too big to succeed or too big to fail. India was on the brink of severe economic failure, desperately in need of a big push.

Robocup Image

Our Novel Approaches

Single Camera Depth Approximation

The robot uses a novel approach for distance approximation using computer vision. In this approach, the robot is able to efficiently approximate the distance from an object or person by analysing its image and comparing it to the size of the respective standard object or body part.

This is helpful in case where there is no other way of depth approximation by ultrasonic waves or Infrared waves sensor system. This technique also enables the robot to tag the person to be followed as well as maintain a formal distance from him/her.

Speech Question Cache-ing

A novel approach for ’question cache-ing’ allows the robot to store the questions and their answers locally based on their frequency of being asked in normal conversations.

Thus, in case of repeating questions, the robot doesn't need to necessarily scrap answers from web but fetch it from local question cache. By utilizing NLP, Anushka can interpret and extract meaning from spoken or written text, enabling it to understand user commands, generate appropriate responses, and engage in natural language conversations.

Facial Feature Forgetfulness

Novel approach for identifying and prioritizing humans in real-time has been applied to the face recognition system to mimic human behavior. The face recognition system uses deep learning Convolutional Neural Network for first creating face embeddings and storing them in local database.

This database is routinely checked for repeating faces and their mapped names. Priority is given to people based on their number of times meeting the robot and time since last meeting. On a routine-base dumping, faces are ”forgotten” if their priority is less, that is, the robot has met the person only once/twice and long time ago.

Vedic Weave

The entire system design and brain's response system of Anushka has been built after a thorough research on the Vedic views of human mind's architecture.

Novel prioritization techniques have been employed in the robot, segregating each data unit as a portion to be remembered or discarded according to the robot's discretion. This quadriplex architecture comes from the vedic texts, and named 'Chitta', 'Manas', 'Ahankaram', 'Buddhi'.

*Note: The usage of novel approaches has been dealt in detail in the Team Description Paper , available for download in Resources section.

Acknowledgements

[1]       Nourbakhsh, I. R., J. Bobenage, et al. (1999). Affective mobile robot educator with a full-time job, Artificial Intelligence, 114, (1-2), 95-124.

[2]       Ioannis Iossi dis1, Christoph Theis, Claudia Grote, Christian Faubel, and Gregor Sch¨oner, “Anthropomorphism as a pervasive design concept for a robotic assistant”, In Proceedings Of The IEEE/RSJ International Conference On Intelligent Robots And Systems (IROS 2003), 2003.

[3]       Scott A. Green, Mark Billinghurst, XiaoQi Chena and J. Geoffrey Chasea, “HumanRobot Collaboration: A Literature Review and Augmented Reality Approach in Design”, International Journal of Advanced Robotic Systems, ISSN 1729-8806, pp. 1-18, Vol. 5, No. 1 2008.

[4]       Miguel Ángel, Salichs, Sanchez-Caballero "Human Inspired Humanoid Robot Control Architecture", Department of Systems Engineering and Automation LeganĂŠs, July 2012.

[5]       Lingling shi, Hiranya Jayakody, Jayantha Katupitiya, “Coordinate control of a DualArm Space Robot”, IEEE Robotics and Automation Magazine, Isuue no.4, Volume 25, pp. 76-85, 2018.

[6]       Avinash Kumar Singh, Neha Baranwal, G. C Nandi, "Development of a self reliant humanoid robot for sketch drawing", 10.1007/s11042-017-4358-x.

[7]       Keitaro Nishimura, Jean Vaz, Paul Oh, "On Humanoid Co-Robot Locomotion when Mechanically Coupled to a Hman Partner", 2018 15th International Conference on Ubiquitous Robots (UR).

[8]       Laura Steffan, Lukas Kaul, Tamim Asfour, “Online stability estimation based on inertial sensor data for human and humanoid fall prevention” , 2017 IEEE-RAS 17th International Conference on Humanoid Robotics, pp. 171-177.

[9]       Erik Berger, David Vogt, Nooshin Haji-Ghassemi, “Inferring guidance information in cooperative human-robot tasks”, 2013 IEEE-RAS 17th International Conference on Humanoid Robotics, pp. 124-129, 2013.

[10]       Shunsuke Kudoh, Koichi Ogawara, Miti Ruchanurucks, Katsushi Ikeuchi, "Painting Robot with Multi-Fingered Hands and Stereo Vision", like2006 IEEE International Conference onMultisensor Fusion and Integration for Intelligent SystemsSeptember 3-6, 2006, Heidelberg, Germany.

Made with ❤️ by Piyush Khanna