Browsing by Author "Stroppa, F."

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Citation - Scopus: 0
Gamifying Haptics User Studies: Comparison of Response Times From Smartphone Interfaces
(Institute of Electrical and Electronics Engineers Inc., 2025) Stroppa, Fabıo; Xu, D.; Sen, U.; Yoshida, K.T.; Stroppa, F.; Nunez, C.M.; Sarac, M.; Computer Engineering
Haptics user studies are often restricted to a set, physical location and use methods that do not captivate the user. Applying game design elements can create an entertaining environment and increase user engagement. Using ubiquitous tools, like smartphones, to conduct haptics user studies could allow researchers to access larger participant groups while a gamified approach could facilitate the data collection by making the experiment more enjoyable. To explore this concept, this work presents a gamified version of an existing psychophysical experiment that investigates response time to multisensory cues using a smartphone based on "Whac-A-Mole". We conducted a user study to compare our gamified interface with an existing psychophysical interface with thirteen participants exploring the response time from eighteen combinations of auditory, haptic, and visual stimuli at different levels of intensities and participant preferences for both interfaces. The results demonstrate that the gamified interface successfully captured similar trends in response times and significantly elevated participant enjoyment p < 0.003), but did not result in equivalent response times to the original interface. This work shows the benefits and drawbacks of following a gamification approach when designing haptics user studies and discusses factors and trade-offs to consider when gamifying studies. © 2008-2011 IEEE.
Citation - Scopus: 10
Shared-Control Teleoperation Paradigms on a Soft-Growing Robot Manipulator
(Institute for Ionics, 2023) Stroppa, F.; Stroppa, Fabıo; Selvaggio, M.; Agharese, N.; Luo, M.; Blumenschein, L.H.; Hawkes, E.W.; Okamura, A.M.; Computer Engineering
Semi-autonomous telerobotic systems allow both humans and robots to exploit their strengths while enabling personalized execution of a remote task. For soft robots with kinematic structures dissimilar to those of human operators, it is unknown how the allocation of control between the human and the robot changes the performance. This work presents a set of interaction paradigms between a human and a remote soft-growing robot manipulator, with demonstrations in both real and simulated scenarios. The soft robot can grow and retract by eversion and inversion of its tubular body, a property we exploit in the interaction paradigms. We implemented and tested six different human-robot interaction paradigms, with full teleoperation at one extreme and gradually adding autonomy to various aspects of the task execution. All paradigms are demonstrated by two experts and two naive operators. Results show that humans and the soft robot manipulator can effectively split their control along different degrees of freedom while acting simultaneously to accomplish a task. In the simple pick-and-place task studied in this work, performance improves as the control is gradually given to the robot’s autonomy, especially when the robot can correct certain human errors. However, human engagement is maximized when the control over a task is at least partially shared. Finally, when the human operator is assisted by haptic guidance, which is computed based on soft robot tip position errors, we observed that the improvement in performance is dependent on the expertise of the human operator. © 2023, The Author(s), under exclusive licence to Springer Nature B.V.
Citation - Scopus: 11
Task-Specific Design Optimization and Fabrication for Inflated-Beam Soft Robots With Growable Discrete Joints
(Institute of Electrical and Electronics Engineers Inc., 2022) Exarchos, I.; Stroppa, Fabıo; Wang, K.; Do, B.H.; Stroppa, F.; Coad, M.M.; Okamura, A.M.; Liu, C.K.; Computer Engineering
Soft robot serial chain manipulators with the capability for growth, stiffness control, and discrete joints have the potential to approach the dexterity of traditional robot arms, while improving safety, lowering cost, and providing an increased workspace, with potential application in home environments. This paper presents an approach for design optimization of such robots to reach specified targets while minimizing the number of discrete joints and thus construction and actuation costs. We define a maximum number of allowable joints, as well as hardware constraints imposed by the materials and actuation available for soft growing robots, and we formulate and solve an optimization problem to output a planar robot design, i.e., the total number of potential joints and their locations along the robot body, which reaches all the desired targets, avoids known obstacles, and maximizes the workspace. We demonstrate a process to rapidly construct the resulting soft growing robot design. Finally, we use our algorithm to evaluate the ability of this design to reach new targets and demonstrate the algorithm's utility as a design tool to explore robot capabilities given various constraints and objectives. © 2022 IEEE.