6 citations · 15 across the 10 of their papers we have counts for
10 papers
Towards Data-Driven Adaptive Exoskeleton Assistance for Post-stroke Gait
Fabian C. Weigend, Dabin K. Choe, Santiago Canete +1
Recent work has shown that exoskeletons controlled through data-driven methods can dynamically adapt assistance to various tasks for healthy young adults. However, applying these m…
SiSCo: Signal Synthesis for Effective Human-Robot Communication Via Large Language Models
Shubham Sonawani, Fabian Weigend, Heni Ben Amor
Effective human-robot collaboration hinges on robust communication channels, with visual signaling playing a pivotal role due to its intuitive appeal. Yet, the creation of visually…
Ubiquitous Robot Control Through Multimodal Motion Capture Using Smartwatch and Smartphone Data
Fabian C Weigend, Neelesh Kumar, Oya Aran +1
We present an open-source library for seamless robot control through motion capture using smartphones and smartwatches. Our library features three modes: Watch Only Mode, enabling…
Enabling Stateful Behaviors for Diffusion-based Policy Learning
Xiao Liu, Fabian Weigend, Yifan Zhou +1
While imitation learning provides a simple and effective framework for policy learning, acquiring consistent actions during robot execution remains a challenging task. Existing app…
iRoCo: Intuitive Robot Control From Anywhere Using a Smartwatch
Fabian C Weigend, Xiao Liu, Shubham Sonawani +3
This paper introduces iRoCo (intuitive Robot Control) - a framework for ubiquitous human-robot collaboration using a single smartwatch and smartphone. By integrating probabilistic…
Probabilistic Differentiable Filters Enable Ubiquitous Robot Control with Smartwatches
Fabian C Weigend, Xiao Liu, Heni Ben Amor
Ubiquitous robot control and human-robot collaboration using smart devices poses a challenging problem primarily due to strict accuracy requirements and sparse information. This pa…
Anytime, Anywhere: Human Arm Pose from Smartwatch Data for Ubiquitous Robot Control and Teleoperation
Fabian C Weigend, Shubham Sonawani, Michael Drolet +1
This work devises an optimized machine learning approach for human arm pose estimation from a single smartwatch. Our approach results in a distribution of possible wrist and elbow…
Benefits and limitations of a new hydraulic performance model
Fabian C. Weigend, Edward Gray, Oliver Obst +1
Purpose: Performance models are important tools for coaches and athletes to optimise competition outcomes or training schedules. A recently published hydraulic performance model ha…
A hydraulic model outperforms work-balance models for predicting recovery kinetics from intermittent exercise
Fabian C. Weigend, David C. Clarke, Oliver Obst +1
Data Science advances in sports commonly involve "big data", i.e., large sport-related data sets. However, such big data sets are not always available, necessitating specialized mo…
A New Pathway to Approximate Energy Expenditure and Recovery of an Athlete
Fabian Clemens Weigend, Jason Siegler, Oliver Obst
This work proposes to use evolutionary computation as a pathway to allow a new perspective on the modeling of energy expenditure and recovery of an individual athlete during exerci…