Assessment of Environmental Effects on Collaborative Haptic Guidance

Khademian, Behzad; Apkarian, Jacob; Hashtrudi-Zaad, Keyvan

doi:10.1162/pres_a_00044

Cited by 9 publications

(5 citation statements)

References 27 publications

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“…Shared control has been studied for different applications of human-machine interaction: For example [2,4,28,40,53] investigated shared control for teleoperation, space and aviation systems, [35][36][37][38] explored similar principles for surgery applications, while [7] and [54] report on shared control for powered wheelchairs.…”

Section: Introductionmentioning

confidence: 99%

An Integrated Decision Making Approach for Adaptive Shared Control of Mobility Assistance Robots

Geravand

Werner

Hauer

et al. 2016

Int J of Soc Robotics

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We recommend you cite the published version. The publisher's URL is: http://dx.doi.org/10.1007/s12369-016-0353-z Refereed: YesThe final publication is available at Springer via http://dx.doi.org/10.1007/s12369?016?0353?z Disclaimer UWE has obtained warranties from all depositors as to their title in the material deposited and as to their right to deposit such material. UWE makes no representation or warranties of commercial utility, title, or fitness for a particular purpose or any other warranty, express or implied in respect of any material deposited. UWE makes no representation that the use of the materials will not infringe any patent, copyright, trademark or other property or proprietary rights. UWE accepts no liability for any infringement of intellectual property rights in any material deposited but will remove such material from public view pending investigation in the event of an allegation of any such infringement. PLEASE SCROLL DOWN FOR TEXT.Noname manuscript No. Abstract Mobility assistance robots (MARs) provide support to elderly or patients during walking. The design of a safe and intuitive assistance behavior is one of the major challenges in this context. We present an integrated approach for the context-specific, on-line adaptation of the assistance level of a rollator-type mobility assistance robot by gain-scheduling of low-level robot control parameters. A human-inspired decision-making model, the Drift-Diffusion Model, is introduced as the key principle to gain-schedule parameters and with this to adapt the provided robot assistance in order to achieve a human-like assistive behavior. The mobility assistance robot is designed to provide a) cognitive assistance to help the user following a desired path towards a predefined destination as well as b) sensorial assistance to avoid collisions with obstacles while allowing for an intentional approach of them. Further, the robot observes the user long-term performance and fatigue to adapt the overall level of c) physical assistance provided. For each type of assistance a decision-making problem is formulated that affects different low-level control parameters. The effectiveness of the proposed approach is demonstrated in technical validation experiments. Moreover, the proposed approach is evaluated in a user study with 35 elderly persons. Obtained results indicate that the proposed gain-scheduling technique incorporating ideas of human decision-making models shows a general high potential for the application in adaptive shared control of mobility assistance robots.

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Section: Introductionmentioning

confidence: 99%

An Integrated Decision Making Approach for Adaptive Shared Control of Mobility Assistance Robots

Geravand

Werner

Hauer

et al. 2016

Int J of Soc Robotics

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“…Through the cooperative robot based on bilateral teleoperation system, we can get rid of the constraints of distance, environment and so on, and complete the task that the operator cannot complete alone. For example, the teleoperation system studied by Khademian et al [52] in 2011 allows trainees and trainers to interact with each other to perform common tasks in a shared virtual environment. In 2013, Shahbazi et al [53] also proposed a teleoperated dual-user system incorporating Virtual Fixtures (VFs) that allows expert and a trainee conduct a robotic surgery at the same time.…”

Section: A Applicationsmentioning

confidence: 99%

A Review of Bilateral Teleoperation Control Strategies with Soft Environment

Deng

Tang

Yang

et al. 2021

2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)

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In the past two decades, bilateral teleoperation with haptic feedback has attracted great research and application interests in both robotics and other areas. Initially triggered by the need to handle dangerous and remote distance tasks such as nuclear materials manipulation and space exploration, bilateral teleoperation has found its way into other applications as a result of development of control theory, robotic technology (both hardware and software) and latest breakthrough in artificial intelligence and machine learning. Consequently, bilateral teleoperation is found facing new challenges brought by these new applications. One major and obvious change is the working environment for the slave manipulator: different from rigid or solid contact environments which are reasonably assumed in early applications in industrial, nuclear and aerospace applications, the slave environment is now more complex and often the objects in contact are much softer in term of stiffness and can not be described by simple elastic model if good teleoperation performance (accurate and transparent) is expected. In this paper, the research of bilateral teleoperation system considering soft environment in recent 20 years has been surveyed for the first time in literature, to the knowledge of the authors. Following the difference in real applications, in this review the definition of soft environment covers linear elastic environment with much lower stiffness than conventional industrial environment and nonlinear complex soft environment with/out time-varying characteristics. Accordingly, the surveyed control strategies and structures in recent literature to improve the stability and accuracy of bilateral teleoperation with soft environment are classified and explained. Finally, the main applications, current challenges and future perspectives of bilateral teleoperation with soft environment are discussed.

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“…(26) can be obtained using Eqs. (24) and (25) when the human input is adversarial and u h = 0, respectively. From the solution of the differential equation in Eq.…”

Section: Convergence Analysismentioning

confidence: 99%

“…For example, in dual-user haptic training system for medical surgery, the control allocation can be chosen according to the expertise of the trainee and the trainer. 4,[23][24][25][26][27] In contrast to fixed control allocation, adaptive control allocation dynamically allocates control authority to the human and the autonomy. The control allocation can be based on human performance, 14,15,28 duration of interaction, 29 safety of the system, 30 agreement between the human and the robot, 16 or the state of the robot in the environment.…”

Section: Introductionmentioning

confidence: 99%

Obstacle avoidance control of a human-in-the-loop mobile robot system using harmonic potential fields

2017

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SUMMARYThis paper considers applications where a human agent is navigating a semi-autonomous mobile robot in an environment with obstacles. The human input to the robot can be based on a desired navigation objective, which may not be known to the robot. Additionally, the semi-autonomous robot can be programmed to ensure obstacle avoidance as it navigates the environment. A shared control architecture can be used to appropriately fuse the human and the autonomy inputs to obtain a net control input that drives the robot. In this paper, an adaptive, near-continuous control allocation function is included in the shared controller, which continuously varies the control effort exerted by the human and the autonomy based on the position of the robot relative to obstacles. The developed control allocation function facilitates the human to freely navigate the robot when away from obstacles, and it causes the autonomy control input to progressively dominate as the robot approaches obstacles. A harmonic potential field-based non-linear sliding mode controller is developed to obtain the autonomy control input for obstacle avoidance. In addition, a robust feed-forward term is included in the autonomy control input to maintain stability in the presence of adverse human inputs, which can be critical in applications such as to prevent collision or roll-over of smart wheelchairs due to erroneous human inputs. Lyapunov-based stability analysis is presented to guarantee finite-time stability of the developed shared controller, i.e., the autonomy guarantees obstacle avoidance as the human navigates the robot. Experimental results are provided to validate the performance of the developed shared controller.

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Assessment of Environmental Effects on Collaborative Haptic Guidance

Cited by 9 publications

References 27 publications

An Integrated Decision Making Approach for Adaptive Shared Control of Mobility Assistance Robots

An Integrated Decision Making Approach for Adaptive Shared Control of Mobility Assistance Robots

A Review of Bilateral Teleoperation Control Strategies with Soft Environment

Obstacle avoidance control of a human-in-the-loop mobile robot system using harmonic potential fields

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