Understanding Interactions for Smart Wheelchair Navigation in Crowds

Zhang, Bingqing; Barbareschi, Giulia; Herrera, Roxana Ramirez; Carlson, Tom; Holloway, Catherine

doi:10.1145/3491102.3502085

Cited by 14 publications

(7 citation statements)

References 58 publications

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“…From the admissible velocities within this dynamic window, the combination of translational and rotational velocities is selected by maximizing an objective function. While there have been a few attempts to apply this approach to wheelchairs [51][52][53][54][55][56][57][58], notable drawbacks include increased computational costs and latency, particularly as the environment becomes more complex. Another widely employed approach for mobile robots is the potential fields method (PFM), with a prominent implementation known as the virtual force field (VFF).…”

Section: Related Workmentioning

confidence: 99%

Design of an Assisted Driving System for Obstacle Avoidance Based on Reinforcement Learning Applied to Electrified Wheelchairs

Pacini,

Dini,

Fanucci

2024

Electronics

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Driving a motorized wheelchair is not without risk and requires high cognitive effort to obtain good environmental perception. Therefore, people with severe disabilities are at risk, potentially lowering their social engagement, and thus, affecting their overall well-being. Therefore, we designed a cooperative driving system for obstacle avoidance based on a trained reinforcement learning (RL) algorithm. The system takes the desired direction and speed from the user via a joystick and the obstacle distribution from a LiDAR placed in front of the wheelchair. Considering both inputs, the system outputs a pair of forward and rotational speeds that ensure obstacle avoidance while being as close as possible to the user commands. We validated it through simulations and compared it with a vector field histogram (VFH). The preliminary results show that the RL algorithm does not disruptively alter the user intention, reduces the number of collisions, and provides better door passages than a VFH; furthermore, it can be integrated on an embedded device. However, it still suffers from higher jerkiness.

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Section: Related Workmentioning

confidence: 99%

Design of an Assisted Driving System for Obstacle Avoidance Based on Reinforcement Learning Applied to Electrified Wheelchairs

Pacini,

Dini,

Fanucci

2024

Electronics

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“…In the first, known as hierarchical shared control, users dictate high-level actions while the wheelchair autonomously handles collision avoidance [40]. The second strategy merges inputs from both the user and the motion planner, moving the wheelchair only when commands from both are present, thereby enhancing user control and collaboration [31,37,41,42]. Guided by these strategies to foster a more suitable human-machine collaboration for shared-control wheelchairs, the user retains higher-level decision-making while allowing the automated system to handle simple driving tasks.…”

Section: Shared-control Wheelchairmentioning

confidence: 99%

“…As these projections integrate real-time environmental changes and present a v color and pattern spectrum, this augmented visual feedback significantly heightens bility and paves the way for a symbiotic human-machine relationship [64,65]. Bingqing Zhang's research introduced four conceptual themes pertinent to au omous wheelchair users: type of information needed, interaction modality, interfac cation, and adaptable design [42]. Based on this, we are considering the types of i mation interfaces and interaction content to provide for autonomous wheelchair u Moreover, it is imperative to consider the dynamics between autonomous wheelc and other road users.…”

Section: On-ground Projection-based Shared Ehmi For Autonomous Wheelc...mentioning

confidence: 99%

“…In line with the insights from Bingqing Zhang's design implications, the interface should be context-responsive, efficiently channel a broad information range, and preclude information saturation. It is paramount that this interface harmoniously integrates into societal settings, emphasizing user empathy and societal receptiveness, thereby nurturing open communication between users and pedestrians [42]. Whether the wheelchair has detected the person.…”

Section: On-ground Projection-based Shared Ehmi For Autonomous Wheelc...mentioning

confidence: 99%

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Shared eHMI: Bridging Human–Machine Understanding in Autonomous Wheelchair Navigation

Zhang,

Song,

Huang

et al. 2024

Applied Sciences

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As automated driving system (ADS) technology is adopted in wheelchairs, clarity on the vehicle’s imminent path becomes essential for both users and pedestrians. For users, understanding the imminent path helps mitigate anxiety and facilitates real-time adjustments. For pedestrians, this insight aids in predicting their next move when near the wheelchair. This study introduces an on-ground projection-based shared eHMI approach for autonomous wheelchairs. By visualizing imminent motion intentions on the ground by integrating real and virtual elements, the approach quickly clarifies wheelchair behaviors for all parties, promoting proactive measures to reduce collision risks and ensure smooth wheelchair driving. To explore the practical application of the shared eHMI, a user interface was designed and incorporated into an autonomous wheelchair simulation platform. An observation-based pilot study was conducted with both experienced wheelchair users and pedestrians using structured questionnaires to assess the usability, user experience, and social acceptance of this interaction. The results indicate that the proposed shared eHMI offers clearer motion intentions display and appeal, emphasizing its potential contribution to the field. Future work should focus on improving visibility, practicality, safety, and trust in autonomous wheelchair interactions.

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“…However, movement control might be limited to pre-dened actions to simplify the cognitive load of the pilot and reduce the complexity of the UI. Ultimately, we argue that a good tenet to follow in the design of parallel system is to give users as much control on each avatar as they need for the intended application, but no more that is needed to facilitate management of multiple avatars simultaneously, in line with the idea of smart systems that can provide assistance as required [35,99].…”

Section: A Dierent Form Of Embodimentmentioning

confidence: 99%

Accessible Parallel Embodiment of Multiple Robotic Avatars in a Cafe

Barbareschi¹,

Kawaguchi

Kato

et al. 2022

XRDS

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Novel technological systems enabling people to control multiple robotic avatars simultaneously could support more accessible ways to multitask. An implementation of a parallel avatar system in a cafe shows that, leveraging their existing skills, remote workers with disabilities were able to utilize the system to control up to four robots, each with a different function, to assist customers in a cafe. The parallel avatar systems expand the agency and the capabilities of disabled workers, while also delivering better experiences to customers.

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Understanding Interactions for Smart Wheelchair Navigation in Crowds

Cited by 14 publications

References 58 publications

Design of an Assisted Driving System for Obstacle Avoidance Based on Reinforcement Learning Applied to Electrified Wheelchairs

Design of an Assisted Driving System for Obstacle Avoidance Based on Reinforcement Learning Applied to Electrified Wheelchairs

Shared eHMI: Bridging Human–Machine Understanding in Autonomous Wheelchair Navigation

Accessible Parallel Embodiment of Multiple Robotic Avatars in a Cafe

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