Related papers: Using an Improved Output Feedback MPC Approach for…
The importance of haptic in-sensor computing devices has been increasing. In this study, we successfully fabricated a haptic sensor with a hierarchical structure via the sacrificial template method, using carbon…
Pseudo-haptics exploit carefully crafted visual or auditory cues to trick the brain into "feeling" forces that are never physically applied, offering a low-cost alternative to traditional haptic hardware. Here, we present a comparative…
Haptic guidance is a powerful technique to combine the strengths of humans and autonomous systems for teleoperation. The autonomous system can provide haptic cues to enable the operator to perform precise movements; the operator can…
The computational burden of model predictive control (MPC) limits its application on real-time systems, such as robots, and often requires the use of short prediction horizons. This not only affects the control performance, but also…
The standard engineering approach when facing uncertainty is modelling. Mixing data from a well-calibrated model with real recordings has led to breakthroughs in many applications of AI, from computer vision to autonomous driving. This type…
This study introduces a haptic shared control framework designed to teach human drivers advanced driving skills. In this context, shared control refers to a driving mode where the human driver collaborates with an autonomous driving system…
In contemporary training for industrial manufacturing, reconciling theoretical knowledge with practical experience continues to be a significant difficulty. As companies transition to more intricate and technology-oriented settings,…
People learn motor activities best when they are conscious of their errors and make a concerted effort to correct them. While haptic interfaces can facilitate motor training, existing interfaces are often bulky and do not always ensure…
Improved surgical skill is generally associated with improved patient outcomes, although assessment is subjective; labour-intensive; and requires domain specific expertise. Automated data driven metrics can alleviate these difficulties, as…
Surgical training involves didactic teaching, mentor-led learning, surgical skills laboratories, and direct exposure to surgery; however, increasing clinical pressures have limited operating room (OR) exposure. This work leverages virtual…
Nonlinear receding horizon model predictive control is a powerful approach to controlling nonlinear dynamical systems. However, typical approaches that use the Jacobian, adjoint, and forward-backward passes may lose fidelity and efficacy…
This paper presents a Nonlinear Model Predictive Control (NMPC) scheme targeted at motion planning for mechatronic motion systems, such as drones and mobile platforms. NMPC-based motion planning typically requires low computation times to…
We present a shared control paradigm that improves a user's ability to operate complex, dynamic systems in potentially dangerous environments without a priori knowledge of the user's objective. In this paradigm, the role of the autonomous…
In this paper, we propose a real-time adaptive prediction method to calculate smooth and accurate haptic feedback in complex scenarios. Smooth haptic feedback is an important task for haptic rendering with complex virtual objects. However,…
Reactions such as gestures, facial expressions, and vocalizations are an abundant, naturally occurring channel of information that humans provide during interactions. A robot or other agent could leverage an understanding of such implicit…
The research aims to expand tactile feedback beyond vibrations to various modes of stimuli, such as indentation, vibration, among others. By incorporating soft material into the design of a novel tactile actuator, we can achieve…
While user's perception & performance are predominantly examined independently in virtual reality, the Action-Specific Perception (ASP) theory postulates that the performance of an individual on a task modulates this individual's spatial &…
Haptic interaction is essential for the dynamic dexterity of animals, which seamlessly switch from an impedance to an admittance behaviour using the force feedback from their proprioception. However, this ability is extremely challenging to…
Realistic simulations of detailed, biophysics-based, multi-scale models require very high resolution and, thus, large-scale compute facilities. Existing simulation environments, especially for biomedical applications, are designed to allow…
Developing kinesthetic haptic devices with advanced haptic rendering capabilities is challenging due to the limitations on driving mechanisms. In this study, we introduce a novel soft electrohydraulic actuator and develop a kinesthetic…