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Past Projects

Robotics for Rehabilitation, Exercise and Assessment in Collaborative Healthcare (RREACH) Lab (link)


Implementation of Safe Fall Control Strategies in Half-Scale Lower Limb Exoskeleton Models

Our first exoskeleton prototype consisted of a model of a triple-link inverted pendulum and a control system, designed and fabricated by an undergraduate Engineering Physics student team at UBC (Jan-April 2016). The mechanical test setup characterized a half-plane and half-scale model of a human body. Three joints of the triple-link inverted pendulum replicated the motion of the hip, knee, and ankle joints. Similar to the three-link model of a human fall, the hip and knee joints of the inverted pendulum were actuated and the ankle was a passive joint. The hip and knee joint angles were read through the actuator’s encoder and the ankle joint angle was read by a potentiometer that was installed at the joint. The controller was programmed to start the safe fall control strategy once the ankle angle passed beyond a specified angle. Therefore, the ankle angle sensor was constantly monitored subsequent to the initialization of the hip and knee joints. When the ankle angle exceeded the specified limit, the position control strategy was activated to control the hip and knee joint angles throughout the fall.

Large deviations were observed between the experimental and optimal values of the joints angular velocity throughout the fall duration. This is mainly due to hardware and software limitations of this prototype.
To address the abovementioned issues and to further improve controller performance a second prototype was built by an undergraduate Mechanical Engineering student team at BCIT (Jan-April 2017). The second prototype includes a scaled and adjustable exoskeleton with the same actuation setup as the first prototype and will execute the fall routine, as well as a release mechanism to zero the system and initiate the fall. Currently, we are working on implementing the developed safe fall strategy in this prototype.

Capstone Teams

UBC, ENPH: Todd Darcie, Oliver Gadsby, Bryan Pawlina, Saman Shariat Jaffari

BCIT, MECH: Mila Karanovic, Victor Chen, Amin Askari

Past Interns and Volunteers

Jessica Bo (UBC, MECH), Carter Fang (UBC, MECH), Florian Denkmeier (MITACS Intern)


FEATHERS: Functional Engagement in Assisted Therapy Through Exercise Robotics

We have created the Robotics for Rehabilitation, Exercise and Assessment in Collaborative Healthcare (RREACH) Lab to focus specifically on biomedical engineering projects involving upper limb therapy for persons with neurological impairment. The lab has robotics and motion capture devices to investigate different ways of designing exercise regimens to create more engaging, context-relevant, and effective experiences for persons undergoing therapy. The RREACH Lab currently is home to the FEATHERS Project.

Currently, we are looking at using immersive virtual reality technologies to design engaging exercise regimens, as well as explore new feedback modalities such as visual error augmentation of upper limb symmetry during bimanual reaching. For more information on the study, please see our Current Open Studies.

Principal Investigator

Dr. Mike Van der Loos, Associate Professor, Department of Mechanical Engineering, UBC

Researchers

Leia Shum
Bulmaro Valdes Benavides

Collaborators

Dr. Nicola Hodges, Professor, School of Kinesiology, UBC
Dr. Tal Jarus, Professor, Department of Occupational Science and Occupation Therapy, UBC
Dr. Elizabeth Croft, Professor, Department of Mechanical Engineering, UBC


SleepSmart: Mattress Sensor Array for Characterization of Biosignals and Movement Events

Sleep disorders affect a large percentage of the population; however, most disorders can only be diagnosed through the use of polysomnography. In this overnight sleep study, patients are asked to sleep in a clinical lab attached to many different machines. In addition, patients might be on a waiting list for up to a year before an available lab time comes up. Current techniques are expensive, uncomfortable, and resource-consuming. In an effort to meet the need for an affordable, at-home sleep monitoring system, SleepSmart was developed. SleepSmart is a mattress sensor topper that leverages arrays of accelerometers and thermistors to acquire dynamic data profiles and temperature distribution. Using the data from the sensors, various information such as sleeping postures, biosignals, movement events can be predicted with machine learning methods. The frequency and magnitude of posture changes can be used to determine sleep quality by calculating the restlessness index. These sensors are all incorporated into a mattress topper which would replace a fitted mattress sheet, allowing for unobtrusive monitoring.

A prototype for SleepSmart has been fabricated, and software implementations are currently being implemented to allow for the characterization of biosignals (heart rate and respiratory rate) as well as improve on the existing temperature sensors, and the classification of movement events. The project is being funded by Kids Brain Health Network, a trans-Canada initiative dedicated to studying children’s brain development, and studies are currently underway in collaboration with the BC Children’s Hospital. The final product will be used to assist in the diagnosis of sleep disorders of children with neurodevelopmental disorders. In addition, SleepSmart will allow clinicians to gather a repository of physiological data that can be used in future analysis to further the understanding of sleep in the pediatric population.

If you’re interested in participating, more details can be found here.

Principal Investigator

Dr. Mike Van der Loos, Associate Professor, Department of Mechanical Engineering, UBC

Researchers

Yi Jui Lee (Alex)

 


Physiological Signal Sensing (2017)

Researcher

Navid Shirzad

Collaborators

Dr. Mike Van der Loos, Associate Professor, Department of Mechanical Engineering, UBC
Dr. Elizabeth Croft, Professor, Department of Mechanical Engineering, UBC


CHARM: Collaborative, Human-focused, Assistive Robotics for Manufacturing (2016)

(Original source)

Helping Manufacturers CHARM Their Way Into New Business

CHARM is a research project that together with General Motors of Canada, is exploring ways of deploying robots in manufacturing environments to enhance workers’ capabilities and make production lines more flexible.

CHARM (Collaborative, Human-focused, Assistive Robotics for Manufacturing) is led by University of British Columbia (UBC) mechanical engineering professor Elizabeth Croft. A leading expert in the cutting-edge field of human-robot interaction, she is also NSERC’s Chair for Women in Science and Engineering for the British Columbia and Yukon Region. Dr. Croft is working with researchers from UBC (Karon Maclean), McGill University (Frank Ferrie) and Université Laval (Clément Gosselin and Denis Laurendeau). The research focusses on the potential for smart machines to improve the ability of workers to handle an increased range of products and operations while improving product quality and worker safety. At a time of fierce global competition, this research could give Canada a significant edge in advanced manufacturing and further develop a highly skilled workforce as the marketplace undergoes rapid change. NSERC is investing $621,000 in the four-year Collaborative Research and Development project.

New developments, innovations, and advancements in robotic technology are paving the way for the use of intelligent robots to enable, support, and enhance the capabilities of human workers in manufacturing environments. While the vast majority of current industrial robots have little to no direct interaction with humans, we envision that future industrial robots will assist people in the workplace, support workers in a variety of tasks, improve manufacturing quality and processes, and increase productivity.

CHARM Website

Principal Investigator

Dr. Elizabeth Croft, Professor, Department of Mechanical Engineering, UBC

Researchers

AJung Moon
Matthew Pan
Ergun Calisgan
Benjamin Blumer

Collaborators

General Motors of Canada Ltd.
Dr. Karon MacLean, Professor, Department of Computer Science, University of British Columbia
Dr. Frank Ferrie, Professor, Department of Electrical and Computer Engineering, McGill University
Dr. Denis Laurendeau, Professor, Department of Electrical and Computer Engineering, Université Laval
Dr. Clément Gosselin, Professor, Department of Mechanical Engineering, Université Laval


Roboethics (2016)

Roboethics is an exciting interdisciplinary field of study that deals with social, ethical, and legal implications of robotics technology. As we gradually bring robots into our homes, offices, hospitals and schools, it is important that we ask and answer questions such as: “what should a robot be allowed to do?” “what kind of relationship should we have with robots?” and “how can we implement socially acceptable behaviours into not only robot designs but also the design process itself?”

At the CARIS lab, we are developing an online community called Open Robotics initiative (ORi) to ask and answer some of these questions and to help roboticists make informed design decisions. In the years to come, ORi plans to tightly link ethics discussion with open-source robot designs to better realise robots that are truly human-friendly.

Researcher

AJung Moon

Collaborators

Dr. Mike Van der Loos, Associate Professor, Department of Mechanical Engineering, UBC
Dr. Elizabeth Croft, Professor, Department of Mechanical Engineering, UBC
Fiorella Operto, President, Scuola di Robotica
Gianmarco Veruggio, Chair of the Scientific Committee , Scuola di Robotica


Weight Distribution Asymmetry and Perception in Sit-to-Stand (2014)

When performing bilateral tasks that require load bearing or force production, post-stroke hemiparetics often rely more on their non-paretic (stronger) side, despite their perception that their weight distribution is even or that they have matched forces equally. This discrepancy implies that force perception and body proprioception may need to be addressed more directly as part of stroke rehabilitation programs.

We are focusing on the motion of rising from a chair, known as “sit-to-stand” (STS), to investigate hemiparetic weight distribution asymmetry and perception in the context of a functional movement. We have developed a closed-loop, load sharing assistive device that supports a specific portion of the user’s body weight while performing the STS motion. We are first interested in characterizing subjects’ weight distribution asymmetry and perception as a function of assistance from the device to see 1) if asymmetry is affected by how much body weight the subject is bearing, and 2) if the (in)accuracy of the subject’s perception is affected by total weight bearing. In a following study, we will compare various feedback types and schedules to determine which are most effective for improving weight distribution asymmetry and which are best for improving weight distribution perception.

Researcher

Jenny Sullivan

Collaborators

Dr. Antony Hodgson, Professor, Department of Mechanical Engineering, UBC
Dr. Elizabeth Croft, Professor, Department of Mechanical Engineering, UBC
Dr. Mike Van der Loos, Associate Professor, Department of Mechanical Engineering, UBC

Other Collaborators

Dr. Yoshiaki Ohkami, Professor, Graduate School of System Design Management, Keio University
Mike Kayo, PhD Candidate, Graduate School of System Design Management, Keio University


Vision Guided Motion Control for Industrial Robots (2013)

Our past work in integrating machine vision technology, industrial systems and robotic applications led to a successful research project with Braintech Canada Inc. on vision guided bin picking, including partnerships with ABB (the world’s largest producer of industrial robots) and Toyota USA. This effort, in partnership with the Laboratory for Computational Intelligence, resulted in industrially appropriate dynamic collision avoidance, visibility computation, visual servoing and grasp planning methods.

We are currently developing strategies for vision guided teach-by-demonstration for industrial manipulators that utilize user demonstrations to generalize the task. We are also developing search strategies applied to “lost targets” in robot visual servoing applications. Our ongoing work on visual servoing for target interception is supported by Hyundai Heavy Industries Robotics Division.

Researchers

Sina Radmard
Ambrose Chan

Collaborators

Hyundai Heavy Industries Co., Ltd.
Prof. Graziano Chesi, Associate Professor, Department of Electrical and Electronic Engineering, University of Hong Kong
Tiantian Shen, PhD Candidate, Department of Electrical and Electronic Engineering, University of Hong Kong


2012

Robot for Interactive Sensory Engagement and Rehabilitation (RISER)
Tom Huryn, M.A.Sc. Candidate
J.-S. Blouin, E. Croft, A. Hodgson and M. Van der Loos, Supervisors

2011

Biomechanical Analysis of Assisted Sit to Stand
Jeswin Jeyasurya, M.A.Sc. Candidate
E. Croft, A. Hodgson and M. Van der Loos, Supervisors

2010

User Intent Based Control in Human-Robot Cooperative Manipulation
Davide De Carli, Laurea Candidate
A. Bicchi, L Pollini and E. Croft, Supervisors

Affect Based Control for Device Interaction
Jeswin Jeyasurya, M.A.Sc. Candidate
E. Croft, A. Hodgson and M. Van der Loos, Supervisors

Strategies for HRI in Non-Structured Environment
Susana Zoghbi, Ph.D. Candidate
E. Croft and M. Van der Loos, Supervisors

2009

Constraint-Aware Visual Servoing for Teaching Practical Robot Motion
Ambrose Chan, M.A.Sc. Candidate
E. Croft and J.Little, Supervisors

Two-Fingered Grasp Planning for Randomized Bin-Picking: Determining the Best Pick
Donna Dupuis, M.A.Sc. Candidate
E. Croft and J. Little, Supervisors

Path Planning for Improved Target Observability
Matthew Baumann, M.Sc. Candidate
J. Little and E. Croft, Supervisors

2007

Dynamic Parameter Identification for the CRS A460 Robot
Kati Radkhah, Visiting Diploma Candidate
D. Kulic and E. Croft, Supervisors

2005

Safety for Human Robot Interaction
Dana Kulic, Ph.D. Candidate
E. Croft, Supervisor

Camera Positioning for robot path tele-training.
Tao Sang, M.A.Sc. Candidate
E. Croft, Supervisor

Cooperative Robotic Sculpting
Bill Owen, Ph.D. Candidate
B. Benhabib and E. Croft, Supervisors

2004

Testing air muscle technology for its applicability to assistive devices for the elderly
Damien Clapa, M.A.Sc. Candidate
E. Croft, Supervisor

Assessing electromyogram controlled air muscles for orthotic devices
Greg Forrest, M.A.Sc. Candidate
A. Hodgson and E. Croft

Haptics interaction with virtual rigid multi-body environment
Daniela Constantinescu, Ph.D. Candidate
S. Salcudean and Dr. E. Croft, Supervisors

Jerk-Limited Trajectory Planning
Sonja Macfarlane, M.Sc. Candidate
E. Croft, Supervisor

Sensing-System Planning for the Surveillance of Moving Objects
Michael Naish, Ph.D. Candidate
B. Behnabib. and E. Croft, Supervisors

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Tel: 604.822.6413
Email:
CARIS Lab
Department of Mechanical Engineering, UBC,
Vancouver, BC, Canada
Tel: 604.822.3147
Fax: 604.822.2403
See contact page for addresses.

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