Communicating Robot Goals via Haptic Feedback in Manipulation Tasks

Pocius, Rey; Zamani, Naghmeh; Culbertson, Heather; Nikolaidis, Stefanos

doi:10.1145/3371382.3377444

Cited by 8 publications

(4 citation statements)

References 12 publications

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“…Vibrotactile feedbacks are vibrations that can provide sensory information about whether the robot is closer or further from an obstacle [22], [23] while squeezing bands can simulate the sensation of grasping objects [24]. Six DoF controllers apply resistance forces to guide the robot's movements, intervening, for instance, if the robot deviates from the intended path [25], [26]. However, those solutions are highly specialized and expensive.…”

Section: A Haptic Feedback In Human-robot Interactionmentioning

confidence: 99%

Latent Space Roadmap for Visual Action Planning of Deformable and Rigid Object Manipulation

Lippi

Poklukar

Welle

et al. 2020

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Haptic feedback is essential for humans to successfully perform complex and delicate manipulation tasks. A recent rise in tactile sensors has enabled robots to leverage the sense of touch and expand their capability drastically. However, many tasks still need human intervention/guidance. For this reason, we present a teleoperation framework designed to provide haptic feedback to human operators based on the data from camera-based tactile sensors mounted on the robot gripper. Partial autonomy is introduced to prevent slippage of grasped objects during task execution. Notably, we rely exclusively on low-cost off-the-shelf hardware to realize an affordable solution. We demonstrate the versatility of the framework on nine different objects ranging from rigid to soft and fragile ones, using three different operators on real hardware.

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Section: A Haptic Feedback In Human-robot Interactionmentioning

confidence: 99%

Latent Space Roadmap for Visual Action Planning of Deformable and Rigid Object Manipulation

Lippi

Poklukar

Welle

et al. 2020

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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“…The experiment consisted of three tasks, the first two tasks being divided each into two subtasks. These tasks are inspired by those found in assessment protocol for prosthetics users such as the Assessment of Capacity for Myoelectric Control (ACMC) [22] and from the Chedoke Arm and Hand Activity Inventory (CAHAI) [23,24], a validated upper-arm functional assessment for stroke recovery, already used in teleoperation experiments [25,26]. The tasks are explained in detail in table 1 and illustrated in figure 1.…”

Section: Protocol Of the Experimentsmentioning

confidence: 99%

Learning to teleoperate an upper-limb assistive humanoid robot for bimanual daily-living tasks

Connan¹,

Sierotowicz²,

Henze³

et al. 2021

Biomed. Phys. Eng. Express

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Objective. Bimanual humanoid platforms for home assistance are nowadays available, both as academic prototypes and commercially. Although they are usually thought of as daily helpers for non-disabled users, their ability to move around, together with their dexterity, makes them ideal assistive devices for upper-limb disabled persons, too. Indeed, teleoperating a bimanual robotic platform via muscle activation could revolutionize the way stroke survivors, amputees and patients with spinal injuries solve their daily home chores. Moreover, with respect to direct prosthetic control, teleoperation has the advantage of freeing the user from the burden of the prosthesis itself, overpassing several limitations regarding size, weight, or integration, and thus enables a much higher level of functionality. Approach. In this study, nine participants, two of whom suffer from severe upper-limb disabilities, teleoperated a humanoid assistive platform, performing complex bimanual tasks requiring high precision and bilateral arm/hand coordination, simulating home/office chores. A wearable body posture tracker was used for position control of the robotic torso and arms, while interactive machine learning applied to electromyography of the forearms helped the robot to build an increasingly accurate model of the participant’s intent over time. Main results. All participants, irrespective of their disability, were uniformly able to perform the demanded tasks. Completion times, subjective evaluation scores, as well as energy- and time- efficiency show improvement over time on short and long term. Significance. This is the first time a hybrid setup, involving myoeletric and inertial measurements, is used by disabled people to teleoperate a bimanual humanoid robot. The proposed setup, taking advantage of interactive machine learning, is simple, non-invasive, and offers a new assistive solution for disabled people in their home environment. Additionnally, it has the potential of being used in several other applications in which fine humanoid robot control is required.

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“…Abi-Farraj et al used haptic feedback to help navigate a robotic arm to a predicted grasping pose among multiple targets [13]. In a similar setup, Pocius et al also proposed to use forces to communicate the shared control's prediction of the human's goal to the human operator [10].…”

Section: A Haptic Shared Controlmentioning

confidence: 99%

“…Therefore, it can be difficult for the human operator to understand how and why their commands are modified by the autonomous assistance, which can lead to low levels of inner compatibility between the human and the shared autonomy system. The reduced transparency of the internal control loop can reduce users' satisfaction and their willingness to use the robot [9], [10]. To address the challenge of balancing the task performance and safety, with system transparency and user satisfaction, we propose a haptic shared autonomy (HSA) teleoperation paradigm.…”

Section: Introductionmentioning

confidence: 99%

Haptic Feedback Improves Human-Robot Agreement and User Satisfaction in Shared-Autonomy Teleoperation

Zhang,

Tron,

Khurshid

2021

Preprint

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Shared autonomy teleoperation can guarantee safety, but does so by reducing the human operator's control authority, which can lead to reduced levels of human-robot agreement and user satisfaction. This paper presents a novel haptic shared autonomy teleoperation paradigm that uses haptic feedback to inform the user about the inner state of a shared autonomy paradigm, while still guaranteeing safety. This differs from haptic shared control, which uses haptic feedback to inform the user's actions, but gives the human operator full control over the robot's actions. We conducted a user study in which twelve users flew a simulated UAV in a search-andrescue task with no assistance or assistance provided by haptic shared control, shared autonomy, or haptic shared autonomy. All assistive teleoperation methods use control barrier functions to find a control command that is both safe and as close as possible to the human-generated control command. For assistive teleoperation conditions with haptic feedback, we apply a force to the user that is proportional to the difference between the human-generated control and the safe control. We find that haptic shared autonomy improves the user's task performance and satisfaction. We also find that haptic feedback in assistive teleoperation can improve the user's situational awareness. Finally, results show that adding haptic feedback to sharedautonomy teleoperation can improve human-robot agreement.

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Communicating Robot Goals via Haptic Feedback in Manipulation Tasks

Cited by 8 publications

References 12 publications

Latent Space Roadmap for Visual Action Planning of Deformable and Rigid Object Manipulation

Latent Space Roadmap for Visual Action Planning of Deformable and Rigid Object Manipulation

Learning to teleoperate an upper-limb assistive humanoid robot for bimanual daily-living tasks

Haptic Feedback Improves Human-Robot Agreement and User Satisfaction in Shared-Autonomy Teleoperation

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