Supernumerary robotic limbs (SRLs) are robotic structures integrated closely with the user's body, which augment human physical capabilities and necessitate seamless, naturalistic human-machine interaction. For effective assistance in physical tasks, enabling SRLs to hand over objects to humans is crucial. Yet, designing heuristic-based policies for robots is time-consuming, difficult to generalize across tasks, and results in less human-like motion. When trained with proper datasets, generative models are powerful alternatives for creating naturalistic handover motions. We introduce 3HANDS, a novel dataset of object handover interactions between a participant performing a daily activity and another participant enacting a hip-mounted SRL in a naturalistic manner. 3HANDS captures the unique characteristics of SRL interactions: operating in intimate personal space with asymmetric object origins, implicit motion synchronization, and the user's engagement in a primary task during the handover. To demonstrate the effectiveness of our dataset, we present three models: one that generates naturalistic handover trajectories, another that determines the appropriate handover endpoints, and a third that predicts the moment to initiate a handover. In a user study (N=10), we compare the handover interaction performed with our method compared to a baseline. The findings show that our method was perceived as significantly more natural, less physically demanding, and more comfortable.

Wearable robotic limbs (WRLs) augment human capabilities through robotic structures that attach to the user’s body. While WRLs are intensely researched and various device designs have been presented, it remains difficult for non-roboticists to engage with this exciting field. We aim to empower interaction designers and application domain experts to explore novel designs and applications by rapidly prototyping personalized WRLs that are customized for different tasks, different body locations, or different users. In this paper, we present WRLKit, an interactive computational design approach that enables designers to rapidly prototype a personalized WRL without requiring extensive robotics and ergonomics expertise. The body-aware optimization approach starts by capturing the user’s body dimensions and dynamic body poses. Then, an optimized fabricable structure of the WRL is generated for a desired mounting location and workspace of the WRL, to fit the user’s body and intended task. The results of a user study and several implemented prototypes demonstrate the practical feasibility and versatility of WRLKit.

This article presents an impedance type ankle haptic interface for providing users with an immersive navigation experience in virtual reality (VR). The ankle platform, actuated by an electric motor with feedback control, enables the use of foot-tapping gestures to create a walking experience like a real one and to haptically render different types of walking terrains. Experimental studies demonstrated that the interface can be easily used to generate virtual walking and is capable of rendering terrains, such as hard and soft surfaces, and multi-layer complex dynamic terrains. The designed system is a seated-type VR locomotion interface, therefore allowing its user to maintain a stable seated posture to comfortably navigate a virtual scene.

We propose a force-feedback brake pedal with series elastic actuation to preserve the conventional brake pedal feel during cooperative regenerative braking. The novelty of the proposed design is due to the deliberate introduction of a compliant element between the actuator and the brake pedal whose deflections are measured to estimate interaction forces and to perform closed-loop force control. Thanks to its series elasticity, the force-feedback brake pedal can utilize robust controllers to achieve high fidelity force control, possesses favorable output impedance characteristics over the entire frequency spectrum, and can be implemented in a compact package using low-cost components. The applicability and effectiveness of the proposed series elastic brake pedal have been tested through human subject experiments that evaluate simulated cooperative regenerative braking scenarios with and without pedal feel compensation. The experimental results and responses to the accompanying questionnaire indicate that pedal feel compensation through the series elastic brake pedal can significantly decrease hard braking instances, improving safety and driver experience.