Bio-inspired Computing for Robots and Music Jim Trresen Research - - PowerPoint PPT Presentation

Bio-inspired Computing for Robots and Music

Jim Tørresen Research group Robotics and Intelligent Systems

Robotics and Intelligent Systems

Robotics and Intelligent Systems (ROBIN)

Jim Tørresen Professor, Group leader Mats Høvin

• Assoc. Prof.

Kyrre Glette

• Assoc. Prof.

Arash Ahmadi (MedFak) Asbjørn Danielsen (UiT) Benedikte Wallace Eivind Samuelsen Farzan Noori Flavia Dias Casagrande (HIOA) Justinas Miseikis Jørgen Nordmoen Sondre Engebråten (FFI) Tønnes Nygaard Yngve Hafting

• Ass. Prof.

Adjunct positions (20%): Alexander Wold (assoc.prof.) Michael Riegler (researcher) Roar Skogstrøm (lecturer) Ståle Skogstad (assoc.prof.) Ole Jakob Elle (assoc.prof.) Students Bachelor ~60; Master: ~45

Robotics and Intelligent Systems program

Students hired on hourly basis Visiting researchers (Brazil) PhD students: Postdocs: Charles Martin Enrique Garcia-Ceja Kai Olav Ellefsen

• Md. Zia Uddin

Weria Khaksar Kristian Nymoen

• Assoc. Prof.

(shared with music dep) Vegard D Søyseth Principal Engineer

Biology Apply principles from nature Applications Robotics Music Health ++ Hardware Electronics 3D-printing Prototyping Robotics and Intelligent Systems

Robotics and Intelligent Systems group ROBIN

Web page: Google for ”ROBIN IFI” Creating systems for demanding run-time environments

Robotics and Intelligent Systems research

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ROBIN

• Methods: Bio-inspired

– Evolutionary computation – Machine learning/deep learning – Prediction – Self-awareness

• Applications:

– Adaptive and evolutionary robotics – Robotic surgery and robots for elderly – Music technology – Mental health support – Reconfigurable (evolvable) hardware

EPEC: Prediction and Coordination for Robots and Interactive Music

Research Council of Norway grant 240862. Goal: Design, implement and evaluate multi-sensor systems that are able to sense, learn and predict future actions and events.

State-of-the-art Rapid Prototyping Facilities

• 3D printers and milling

machines

• Large potential for

developing innovative robot systems.

Robot Design, Simulation, Assembly and Evaluation

• Work with real robots and simulations.
• Reduce gap between simulation and reality.
• Create novel methods for design (e.g., evolution) and

dynamic body shapes (morphology).

Evolved Control Systems

• We can evolve movement patterns!

– Parameterize periodic functions for each joint – Evolve all those parameters

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Evolved Robot Design

• Robot bodies could be difficult to design by

hand.

• We use evolutionary algorithm to evolve both

body and control system simultaneously.

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Video Reuters http://uk.reuters.com/video/2015/06/15/3d- printed-robots-adapt-themselves-to- th?videoId=364592612

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Dyret: A low-cost self-modifying quadruped

• Our most advanced legged

robot to date

• Used for evolutionary

experiments and research in self modelling and control

• Used in master’s projects.

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Robot Surgery (Oslo University Hospital)

Ole Jakob Elle (ROBIN)

• 2. november 2018

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Environment Aware Robot for Hospitals

Goal: allow the fluoroscopy (C- arm) and ultrasound robots to coexist in surgery room without having any direct communication 3D cameras are used to identify and detect robots in the surgery room UR5 robot tries to adapt to changes in the environment and move out of the way when needed

MECS: Multi-sensor Elderly Care Systems

Research Council of Norway grant 247697

Goal: Create and evaluate multimodal mobile human supportive systems that are able to sense, learn and predict future events.

http://www.mn.uio.no/ifi/forskning/prosjekter/mecs

Elderly Care with Robot Companion

• Move from permanent and fixed room

surveillance to flexible and adaptive

– Increased privacy – Increased accuracy

• Active testing involving real environments
• Detect and predict falls and other non-

normal situations to notify caregiver.

– In emergency situations, the robot – rather than the elderly – activates the safety alarm.

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MECS Research

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User needs and preferences

Robot control Robot sensing

Navigation without a Map

• Having a mobile robot with 3D

camera and/or Lidar.

• Moving

in a completely unknown environment.

• Using the sensory information

to build the path and navigate.

• Employing

several AI tools including Fuzzy Logic and Genetic Algorithm Challenge:

• Finding computationally cheap

solutions with high quality.

• Deep Learning for

body skeleton tracking in real-time.

• 3-d body modeling

in real-time.

Real-time Tracking, Segmentation, and Modelling

Real-time Face Tracking

• Face tracking in real-

time using RGB camera on a robot.

• Works well when

there is enough light.

• Face tracking in real-

time using thermal camera on a robot.

• Works well even in

the dark.

Ultra-Wide Band (UWB) radar sensor see through walls

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INTROMAT: INtroducing personalized TReatment Of Mental health problems using Adaptive Technology (2016-2022)

Goal: Increase access to mental health services for common mental health problems by developing smartphone technology which can guide patients.

Funding: IKTPLUSS Lighthouse, Research Council of Norway

http://intromat.no

Mental health monitoring (INTROMAT)

• Analysis of sensor and behavioral data with

machine learning.

• Mental states prediction for bipolar, anxiety and

attention-deficit/hyperactivity disorders.

• Use of smartphones, wristwatches and virtual

reality devices to monitor users´ behavior.

• Adapt clinical follow up and activate automatic

treatments when needed.

Mental state

Speech, motion, heartbeat, phone usage etc Machine learning

5 cases

• Relapse prevention for bipolar disorder
• Cognitive training in Attention Deficit

Hyperactivity Disorder (ADHD)

• Job-focused treatment for depression in

adults

• Early intervention and treatment for

social anxiety disorder in adolescents

• Psycho-social support for women

recovering from gynecological cancer.

International Collaboration

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Study Abroad? – Master Project in Brazil, Japan or US

• Funding available for selected students to

do two semesters abroad for master thesis

• work. Apply at/before November 1
• Funding through collaboration projects

(2017–2019) between ROBIN at University

• f Oslo and partners in Brazil, Japan and

(US)

• Cover: Travel + monthly scholarship of

NOK 6000

• Interested? See:

Contact: Jim, e-mail: jimtoer@ifi.uio.no

• 2. november 2018

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http://www.mn.uio.no/ifi/studier/masterop pgaver/robin/study-abroad-coinmac.html

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9th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics 19-22 August 2019, Oslo, Norway Web page: https://icdlepirob2019.wordpress.com Call for Papers/Workshop/Tutorials

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https://youtu.be/m5yu2BimALk