Marc Carmichael received his B.Eng. Mechanical and Mechatronic Engineering (2008) and PhD degree (2013) in the area of robotics from the University of Technology Sydney. He joined the UTS Centre for Autonomous Systems (UTS:CAS) as a Lecturer in 2016.
Can supervise: YES
Physical human-robot interaction
Robot kinematics and control
Robot system design
- Dynamics and Control
- Mechanical and Mechatronic Design
Solanes, JE, Gracia, L, Muñoz-Benavent, P, Valls Miro, J, Carmichael, MG & Tornero, J 2018, 'Human–robot collaboration for safe object transportation using force feedback', Robotics and Autonomous Systems, vol. 107, pp. 196-208.View/Download from: Publisher's site
© 2018 Elsevier B.V. This work presents an approach based on multi-task, non-conventional sliding mode control and admittance control for human–robot collaboration aimed at handling applications using force feedback. The proposed robot controller is based on three tasks with different priority levels in order to cooperatively perform the safe transportation of an object with a human operator. In particular, a high-priority task is developed using non-conventional sliding mode control to guarantee safe reference parameters imposed by the task, e.g., keeping a load at a desired orientation (to prevent spill out in the case of liquids, or to reduce undue stresses that may compromise fragile items). Moreover, a second task based on a hybrid admittance control algorithm is used for the human operator to guide the robot by means of a force sensor located at the robot tool. Finally, a third low-priority task is considered for redundant robots in order to use the remaining degrees of freedom of the robot to achieve a pre-set secondary goal (e.g., singularity avoidance, remaining close to a homing configuration for increased safety, etc.) by means of the gradient projection method. The main advantages of the proposed method are robustness and low computational cost. The applicability and effectiveness of the proposed approach are substantiated by experimental results using a redundant 7R manipulator: the Sawyer collaborative robot.
Carmichael, MG, Liu, D & Waldron, KJ 2017, 'A framework for singularity-robust manipulator control during physical human-robot interaction', INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, vol. 36, no. 5-7, pp. 861-876.View/Download from: Publisher's site
Carmichael, MG & Liu, D 2013, 'Estimating Physical Assistance Need Using a Musculoskeletal Model', IEEE Transactions On Biomedical Engineering, vol. 60, no. 7, pp. 1912-1919.View/Download from: Publisher's site
Technologies that provide physical assistance during tasks are often required to provide assistance specific to the task and person performing it. An example is robotic rehabilitation in which the assistance-as-needed (AAN) paradigm aims to provide operators with the minimum assistance required to perform the task. Current approaches use empirical performance-based methods which require repeated observation of the specific task before an estimate of the needed assistance can be determined. In this paper, we present a new approach utilizing a musculoskeletal model (MM) of the upper limb to estimate the operator's assistance needs with respect to physical tasks. With capabilities of the operator defined at the muscular level of the MM, an optimization model is used to estimate the operator's strength capability. Strength required to perform a task is calculated using a task model. The difference or gap between the operator's strength capability and the strength required to execute a task forms the basis for the new AAN paradigm. We show how this approach estimates the effects of limb pose, load direction, and muscle impairments on a person's ability to perform tasks.
Lai, Y, Sutjipto, S, Carmichael, M & Paul, G 2019, 'Heuristic Detection of Recovery Progress Using Robotic Data', 2019 IEEE 9th International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM), Bangkok, Thailand.
Carmichael, MG, Aldini, S, Khonasty, R, Tran, A, Reeks, C, Liu, D, Waldron, KJ & Dissanayake, G 2019, 'The ANBOT: An Intelligent Robotic Co-worker for Industrial Abrasive Blasting', IEEE International Conference on Intelligent Robots and Systems, IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, Macau, China, pp. 8026-8033.View/Download from: Publisher's site
© 2019 IEEE. We present the ANBOT, an intelligent robotic coworker for physical human-robot collaboration. The ANBOT system assists workers performing industrial abrasive blasting, shielding them from the large forces experienced during this physically demanding task. The co-operative robotic system combines the strength and endurance of robots with the decision making of skilled workers. The inherent challenges in human-robot collaboration, combined with the difficult blasting environment required novel design decisions to be made and new solutions to be developed. These include an approach for handling kinematic singularities in a manner suitable for human-robot co-operation, estimating worker pose under poor visibility conditions, and an intuitive control scheme that adapts the robotic assistance based on the estimated strength of the worker. In this work we summarise the ANBOT system and present findings from preliminary site trials. The trials included several real industrial blasting tasks under the control of a skilled abrasive blasting worker who had no experience working alongside a robot. Results demonstrate the suitability of the ANBOT for practical industrial applications.
Singh, AK, Aldini, S, Leong, D, Wang, YK, Carmichael, MG, Liu, D & Lin, CT 2020, 'Prediction Error Negativity in Physical Human-Robot Collaboration', 8th International Winter Conference on Brain-Computer Interface, BCI 2020.View/Download from: Publisher's site
© 2020 IEEE. Cognitive conflict is a fundamental phenomenon of human cognition, particularly during interaction with the real world. Understanding and detecting cognitive conflict can help to improve interactions in a variety of applications, such as in human-robot collaboration (HRC), which involves continuously guiding the semi-autonomous robot to perform a task in given settings. There have been several works to detect cognitive conflict in HRC but without physical control settings. In this work, we have conducted the first study to explore cognitive conflict using prediction error negativity (PEN) in physical human-robot collaboration (pHRC). Our results show that there was a statistically significant (p =. 047) higher PEN for conflict condition compared to normal conditions, as well as a statistically significant difference between different levels of PEN (p =. 020). These results indicate that cognitive conflict can be detected in pHRC settings and, consequently, provide a window of opportunities to improve the interaction in pHRC.
Lai, Y, Sutjipto, S, Clout, M, Carmichael, M & Paul, G 2018, 'GAVRe2: Towards Data-driven Upper-Limb Rehabilitation with Adaptive-Feedback Gamification', 2018 IEEE International Conference on Robotics and Biomimetics (ROBIO), IEEE International Conference on Robotics and Biomimetics, IEEE, Kuala Lumpur, Malaysia, pp. 164-169.View/Download from: Publisher's site
This paper presents Game Adaptive Virtual Reality Rehabilitation (GAVRe2), a framework to augment upper limb rehabilitation using Virtual Reality (VR) gamification and haptic robotic manipulator feedback. GAVRe2 integrates independent systems in a modular fashion, connecting patients with therapists remotely to increase patient engagement during rehabilitation.
GAVRe2 exploits VR capabilities to not only increase the productivity of therapists administering rehabilitation, but also to improve rehabilitation mobility for patients. Conventional rehabilitation requires face-to-face physical interactions in a clinical setting which can be inconvenient for patients. The GAVRe2 approach provides an avenue for rehabilitation in a
domestic setting by remotely customizing a routine for the patient. Results are then reported back to therapists for data analysis and future training regime development.
GAVRe2 is evaluated experimentally through a system that integrates a popular VR system, a RGB-D camera, and a collaborative industrial robot, with results indicating potential benefits for long-term rehabilitation and the opportunity for upper limb rehabilitation in a domestic setting.
Aldini, S, Akella, A, Singh, A, Wang, Y-K, Carmichael, M, Liu, D & Lin, C-T 2019, 'Effect of Mechanical Resistance on Cognitive Conﬂict in Physical Human-Robot Collaboration', https://ieeexplore.ieee.org/xpl/conhome/8780387/proceeding, International Conference on Robotics and Automation, IEEE, Canada, pp. 6137-6143.View/Download from: Publisher's site
Physical Human-Robot Collaboration (pHRC) is about the interaction between one or more human operator(s) and one or more robot(s) in direct contact and voluntarily exchanging forces to accomplish a common task. In any pHRC, the intuitiveness of the interaction has always been a priority, so that the operator can comfortably and safely interact with the robot. So far, the intuitiveness has always been described in a qualitative way. In this paper, we suggest an objective way to evaluate intuitiveness, known as prediction error negativity (PEN) using electroencephalogram (EEG). PEN is defined as a negative deflection in event related potential (ERP) due to cognitive conflict, as a consequence of a mismatch between perception and reality. Experimental results showed that the forces exchanged between robot and human during pHRC modulate the amplitude of PEN, representing different levels of cognitive conflict. We also found that PEN amplitude significantly decreases (p <; 0.05) when a mechanical resistance is being applied smoothly and more time in advance before an invisible obstacle, when compared to a scenario in which the resistance is applied abruptly before the obstacle. These results indicate that an earlier and smoother resistance reduces the conflict level. Consequently, this suggests that smoother changes in resistance make the interaction more intuitive.
Aldini, S, Carmichael, MG & Liu, D 2019, 'A Risk Reduction Framework for Design of Physical Human-Robot Collaboration', https://ssl.linklings.net/conferences/acra/acra2019_proceedings/views/b…, Australasian Conference on Robotics and Automation, Adelaide.
As robots designed to physically interact with humans become common in various application areas, shared workspaces and force exchange between human and robot lead to new challenges in terms of safety.
Often, a variety of safety techniques is necessary, and deciding what methods to include in a comprehensive safety framework is not an easy task. This paper is concerned with the design of robotic co-wokers that involve physical Human-Robot Collaboration (pHRC), with humans and robots in continuous direct physical contact and exchanging forces.
A hierarchical risk reduction framework is presented for guiding the design of robotic co-workers to reduce the risk associated with hazards commonly found in pHRC tasks. A case study is presented to demonstrate the use of the framework in designing an Assistance-as-Needed roBOT (ANBOT) which has been extensively tested in practical industry applications.
Hyun, JS, Carmichael, MG, Tran, A, Zhang, S & Liu, D 2019, 'Evaluation of fast, high-detail projected light 3D sensing for robots in construction', Proceedings of the 14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019, IEEE Conference on Industrial Electronics and Applications, IEEE, Xi'an, China, pp. 1262-1267.View/Download from: Publisher's site
© 2019 IEEE. Robots used on-site in construction need to perceive the surrounding environment to operate autonomously. This is challenging as the construction environment is often less than ideal due to changing lighting conditions, turbid air, and the need to detect fine details. In this work we evaluate a custom made projected light 3D sensor system for suitability and practicality in enabling autonomous robotics for construction. A series of tests are performed to evaluate the sensor based on ability to capture environmental details, operate robustly in challenging lighting conditions, and make accurate geometric measurements. Analysis shows that high fidelity measurements with accuracy in the order of millimeters can be obtained, making the technology a promising solution for robots operating in construction environments.
Tran, A, Liu, D, Ranasinghe, R & Carmichael, M 2018, 'Identifying Human Hand Orientation around a Cylindrical Handlebar for physical Human-Robot Interaction', International Symposium on Robotics, Munich, pp. 427-434.
Tran, A, Liu, D, Ranasinghe, R & Carmichael, M 2018, 'Method for Quantifying a Robot's Confidence in its Human Co-worker in Human-Robot Cooperative Grit-Blasting', International Symposium on Robotics, Munich, pp. 474-481.
Carmichael, MG, Aldini, S & Liu, D 2017, 'Human user impressions of damping methods for singularity handling in human-robot collaboration', Australasian Conference on Robotics and Automation, ACRA, Australasian Conference on Robotics and Automation, ARAA, Australia, pp. 107-113.
Kinematic singularity is a fundamental and well understood problem of robot manipulators, with many methods having been developed to ensure safe and robust operation in proximity to singularity. However little attention has been given to the scenario where the robot and human are working in physical contact to collaboratively perform a task. In such a scenario the feelings and impressions of the human operator should be considered when developing solutions for handling singularity. This work presents an experimental study comparing three modes of handling kinematic singularities with respect to the impressions of the human operator. Two of the modes are based on traditional Damped-Least-Squares. The third method uses an asymmetric damping behavior proposed as being well suited for applications involving physical human-robot interaction. The three modes are tested and compared by subjects performing a mock industrial task, and feedback from the subjects analyzed to identify the preferred mode. Results indicate that the choice of method used affects the user's impressions of the interaction, and the asymmetrical damping behavior can produce a preferred interaction experience with human operators during tasks.
Khonasty, R, Carmichael, MG, Liu, D & Aldini, S 2017, 'Effect of External Force and Bimanual Operation on Upper Limb Pose during Human-Robot Collaboration', Australasian Conference on Robotics and Automation 2017, Australasian Conference on Robotics and Automation, ARAA, Sydney Australia, pp. 1-9.
During physical Human-Robot Interaction
(pHRI) in industrial applications such as
human-robot collaborative abrasive blasting,
the operator often interacts with the robot using
two hands, exchanging forces through handle
bars. For the robot to provide appropriate
assistance to the operator and for safe interaction,
it would be beneficial for the robot
to know the pose of the user. This problem
is often challenging due to environmental factors,
limited sensing capability in the environment
and the robot, and redundancy of the human
upper-limb. This paper presents experimental
study on how two-hand interaction and
force exchange affect the operators upper-limb
pose, which can be characterized by swivel angle.
The poses of ten subjects were recorded as
they interacted with a collaborative robot. Differences
in the adopted upper limb pose were
analyzed with respect to factors such as unimanual
versus bimanual operation, and the amplitude
of interaction force between an operator
and the robot. The results discovered that the
the effect of bimanual operation on the upper
limb pose differs between individuals and the
magnitude of the force had a varying effect on
the pose. The requirement of applying a force
forward produced an overall lower swivel angle
Khonasty, R, Carmichael, MG, Liu, D & Waldron, K 2017, 'Upper Body Pose Estimation Utilizing Kinematic Constraints from Physical Human-Robot Interaction', Australasian Conference on Robotics and Automation 2017, Australasian Conference on Robotics and Automation, ARAA, Sydney Australia, pp. 1-10.
In physical Human-Robot Interaction (pHRI),
knowing the pose of the operator is beneficial
and may allow the robot to better accommodate
the human operator. Due to a
large redundancy in the human body, determining
the pose of the human operator is difficult
to achieve in unstructured environments
especially in human-robot collaborative operations
where the robot often occludes the human
from vision-based sensors. This work presents
an upper body pose estimation method based
on exploiting known positions of the human operator's
hands while performing a task with the
robot. Upper body pose is estimated using upper
limb kinematic models alongside sensor information
and model approximations to produce
solutions that are biomechanically feasible.
The pose estimation method was compared
to upper body poses obtained using a motion
capture system. It was shown to be able to
perform robustly with varying amounts of available
information. This approach is well suited
in applications where robots are controlled using
well-defined interfaces such as handlebars,
operating in unstructured environments.
Reeks, C, Carmichael, M, Liu, D & Waldron, K 2016, 'Angled sensor configuration capable of measuring tri-axial forces for pHRI', Proceedings - IEEE International Conference on Robotics and Automation, IEEE International Conference on Robotics and Automation, IEEE, Stockholm, Sweden, pp. 3089-3094.View/Download from: Publisher's site
This paper presents a new configuration for single axis tactile sensor arrays molded in rubber to enable tri-axial force measurement. The configuration requires the sensing axis of each sensor in the array to be rotated out of alignment with respect to external forces. This angled sensor array measures shear forces along axes in a way that is different to a planar sensor array. Three sensors using the angled configuration (22.5°, 45° and 67.5°) and a fourth sensor using the planar configuration (0°) have been fabricated for experimental comparison. Artificial neural networks were trained to interpret the external force applied along each axis (X, Y and Z) from raw pressure sensor values. The results show that the angled sensor configuration is capable of measuring tri-axial external forces with a root mean squared error of 1.79N, less error in comparison to the equivalent sensor utilizing the planar configuration (4.52N). The sensors are then implemented to control a robotic arm. Preliminary findings show angled sensor arrays to be a viable alternative to planar sensor arrays for shear force measurement; this has wide applications in physical Human Robot Interaction (pHRI).
Woolfrey, JK, Liu, DK & Carmichael, M 2016, 'Kinematic Control of an Autonomous Underwater Vehicle-Manipulator System Using Autoregressive Prediction of Vehicle Motion and Model Predictive Control', Proceedings - IEEE International Conference on Robotics and Automation, IEEE International Conference on Robotics and Automation, IEEE, Stockholm, Sweden.View/Download from: Publisher's site
Carmichael, MG & Liu, D 2013, 'Human Biomechanical Model Based Optimal Design of Assistive Shoulder Exoskeleton', Field and Service Robotics, International Conference on Field and Service Robotics, Springer, Brisbane, QLD, Australia, pp. 245-258.View/Download from: Publisher's site
Carmichael, MG & Liu, D 2015, 'Upper Limb Strength Estimation of Physically Impaired Persons using a Musculoskeletal Model: A Sensitivity Analysis', Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, Milan, Italy, pp. 2438-2441.View/Download from: Publisher's site
Sensitivity of upper limb strength calculated from a musculoskeletal model was analyzed, with focus on how the sensitivity is affected when the model is adapted to represent a person with physical impairment. Sensitivity was calculated with respect to four muscle-tendon parameters: muscle peak isometric force, muscle optimal length, muscle pennation, and tendon slack length. Results obtained from a musculoskeletal model of average strength showed highest sensitivity to tendon slack length, followed by muscle optimal length and peak isometric force, which is consistent with existing studies. Muscle pennation angle was relatively insensitive. The analysis was repeated after adapting the musculoskeletal model to represent persons with varying severities of physical impairment. Results showed that utilizing the weakened model significantly increased the sensitivity of the calculated strength at the hand, with parameters previously insensitive becoming highly sensitive. This increased sensitivity presents a significant challenge in applications utilizing musculoskeletal models to represent impaired individuals.
Carmichael, MG, Khonasty, R & Liu, D 2015, 'A Multi-stage Design Framework for the Development of Task-specific Robotic Exoskeletons', Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, Milan, Italy.View/Download from: Publisher's site
Tran, A, Liu, D, Ranasinghe, R, Carmichael, M & Liu, C 2015, 'Analysis of Human grip strength in physical Human Robot Interaction', Proceedings - Analysis of Human grip strength in physical Human Robot Interaction, Conference on Applied Human Factors and Ergonomics, ELSEVIER SCIENCE BV, Las Vegas.View/Download from: Publisher's site
The purpose of this paper is to explore how an operator's grip plays a role in physical Human Robot Interaction (pHRI). By considering how the operator reacts to or initiates changes in control, it is possible to study the operator's grip pattern. By analyzing the grip pattern, it is possible to incorporate their natural response in order to create safer and more intuitive interfaces. An experiment where an exoskeleton and human collaborate in order to complete a path following task has been chosen to observe the forces applied by the user at the handle to determine the interaction between the operator and robot. A ThruMode Matrix Array sensor has been wrapped around the robot's handle to measure the applied pressure. By introducing the sensor it not only enables the measurement of the applied forces and how they are applied but also a measure of how tight the user is gripping the handle. Previous studies show that the natural response of a human to an unexpected event is to tighten their grip, indicating that how an operator grasps the handle can be related to the operator's intention. In order to investigate how the operator's grip of the handle changes, the experiments presented in this paper examine two different scenarios which might occur during an interaction, the first where the robot attempts to deviate from the path and the second where the operator wishes to deviate to a new path. The results of the experiments show that whether the operator or the robot initiates the transition, a measurable change in how the operator grasps the handle. The information in this paper can lead to new applications in pHRI by exploring the possible uses of an operator's grasping strength.
Carmichael, MG, Moutrie, B & Liu, D 2014, 'A Framework for Task-Based Evaluation of Robotic Coworkers', 2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014, International Conference on Control, Automation, Robotics and Vision, IEEE, Singapore, pp. 1362-1367.View/Download from: Publisher's site
Compared to a robotic system that performs a task alone, a robot coworker performing tasks in collaboration with a human operator is subject to additional constraints which can limit the ability of the system to perform the task as required. This work presents a framework for analyzing the ability of a robotic coworker to perform specific tasks in collaboration with a human. The framework allows systematic evaluation of robotic systems based on traditional robot performance measures such as reachable workspace and payload capacity, as well as considering additional factors which arise due to the task being performed collaboratively with a human; such as the reach and strength of the human, human-robot collision, and satisfying desired assistance paradigms. Application of the framework is demonstrated in a case study analyzing a robot designed to assist a human during a materials handling task.
Carmichael, MG & Liu, D 2013, 'Admittance Control Scheme for Implementing Model-based Assistance-As-Needed on a Robot', 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, Osaka, Japan, pp. 870-873.View/Download from: Publisher's site
A model-based assistance-as-needed paradigm has been developed to govern the assistance provided by an assistive robot to its operator. This paradigm has advantages over existing methods of providing assistance-as-needed for applications such as robotic rehabilitation. However, implementation of the model-based paradigm requires a control scheme to be developed which controls the robot so as to provide the assistance calculated by the model-based paradigm to its operator. In this paper an admittance control scheme for providing model-based assistance-as-needed is presented. It is developed considering its suitability for human-robot interaction, and its role within the model-based assistance-as-needed framework. Results from the control implemented on an example robot showed it is capable of providing the operator with the desired level of assistance as governed by the model-based paradigm. This is an essential requirement for the paradigm to be capable of providing efficacious assistance-as-needed in applications such as robotic rehabilitation.
Carmichael, MG & Liu, D 2013, 'Experimental Evaluation of a Model-based Assistance-As-Needed Paradigm using an Assistive Robot', 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, Osaka, Japan, pp. 866-869.View/Download from: Publisher's site
In robotic rehabilitation a promising paradigm is assistance-as-needed. This is because it promotes patient active participation which is essential for neuro-rehabilitation. A model-based assistance-as-needed paradigm has been developed which utilizes a musculoskeletal model representing the subject to calculate their assistance needs. In this paper we experimentally evaluate this model-based paradigm to control an assistive robot and provide a subject with assistance-as-needed at the muscular level. A subject with impairments defined in specific muscle groups performs a number of upper limb tasks, whilst receiving assistance from a robotic exoskeleton. The paradigm is evaluated on its ability to provide assistance only as the subject needs, depending on the tasks being performed and the impairments defined. Results show that the model-based assistance-as-needed paradigm was relatively successful in providing assistance when it was needed.
Carmichael, MG & Liu, D 2012, 'A Task Description Model for Robotic Rehabilitation', 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, International Conference of the IEEE Engineering in Medicine and Biology Society, The Printing House, San Diego, CA, pp. 3086-3089.View/Download from: Publisher's site
The desire to produce robots to aid in physical neurorehabilitation has led to the control paradigm Assistance- As-Needed. This paradigm aims to assist patients in performing physical rehabilitation tasks whilst providing the least amount of assistance required, maximizing the patients effort which is essential for recovery. Ideally the provided assistance equals the gap between the capability required to perform the task and the patients available capability. Current implementations derive a measure of this gap by critiquing task performance based on some criteria. This paper presents a task description model for tasks performed by a patients limb, allowing physical requirements to be calculated. Applied to two upper limb tasks typical of rehabilitation and daily activities, the effect of task variations on the tasks physical requirements are observed. It is proposed that using the task description model to compensate for changing task requirements will allow better support by providing assistance closer to the true needs of the patient
Carmichael, MG & Liu, D 2011, 'Towards using Musculoskeletal Models for Intelligent Control of Physically Assistive Robots', International Conference of the IEEE Engineering in Medicine and Biology Society, International Conference of the IEEE Engineering in Medicine and Biology Society, The Printing House, Boston, MA, pp. 8162-8165.View/Download from: Publisher's site
With the increasing number of robots being developed to physically assist humans in tasks such as rehabilitation and assistive living, more intelligent and personalized control systems are desired. In this paper we propose the use of a musculoskeletal model to estimate the strength of the user, from which information can be utilized to improve control schemes in which robots physically assist humans. An optimization model is developed utilizing a musculoskeletal model to estimate human strength in a specified dynamic state. Results of this optimization as well as methods of using it to observe muscle-based weaknesses in task space are presented. Lastly potential methods and problems in incorporating this model into a robot control system are discussed.
Carmichael, MG, Liu, D & Waldron, K 2010, 'Investigation of Reducing Fatigue and Musculoskeletal Disorder with Passive Actuators', Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, Taipei, Taiwan, pp. 2481-2486.View/Download from: Publisher's site
Robotic systems such as exoskeletons can be effectively used in the reduction of fatigue and musculoskeletal disorders (MSD) associated with physical tasks, but robots which work in physical contact with humans pose problems with user safety. A novel approach to developing intrinsically safe robots is to use passive actuators which have the advantage of being safer, ensuring stability, high force/weight ratios and lower power consumption. It is however not clear how effective an exoskeleton utilizing passive actuators would be in reducing fatigue and the risk of MSD. This paper analyzes the benefit of using such a system with results from dynamic simulations and an experiment using a specially designed mechanism used for evaluation. Results indicate that fatigue and effort could be reduced if robot impedance is minimized. Experiments also highlighted issues of implementing such a system into practice.
Behrens, MJ, Carmichael, MG & Patel, MN 2008, 'Designing SANDRA: An Autonomous Tour Guide Robot for the University of Technology, Sydney', 2008 Australasian Conference on Robotics & Automation, Australasian Conference on Robotics and Automation, Australian Robotics and Automation Association, Canberra, pp. 1-7.
This paper describes how a team of final year mechatronic engineering students developed an autonomous robotic system intended to act as a tour guide during events such as University open days and explores the opportunities this project presented to extend their knowledge and skills. The specifications of the project required the system to localise and navigate autonomously within a known environment while avoiding collisions with any people or obstacles not included in the prior area map. In addition to these requirements, the system needed to locate humans as potential clients, approach and greet them, offer directions and if required take the guest on a guided tour of the university. While taking the subject Advanced Robotics the students were able to develop a functional first prototype of the system and carry out initial tests. Following the completion of the subject a small number of the students opted to continue working on the project developing a second prototype using the knowledge gained and further enhancing their learning experiences. While this project mainly involved integrating existing well known algorithms, software and hardware, it provided an excellent opportunity to enhance the mechatronic engineering skills of the students involved.
Kwok, N, Carmichael, MG, Ha, QP & Tan, K 2007, 'Statistical decision based gray-level image feature matching', Proceedings of the 8th International Conference on Intelligent Technologies (InTech'07), International Conference on Intelligent Technologies, University of Technology Sydney, Sydney, Australia, pp. 269-274.