Kevin Tanghe — accepted AI-conference papers

2018

Realtime Delayless Estimation of Derivatives of Noisy Sensor Signals for Quasi-Cyclic Motions With Application to Joint Acceleration Estimation on an Exoskeleton

Kevin Tanghe, Erwin Aertbeliën, Jonas Vantilt, Marta Moltedo, Tomislav Bacek, Dirk Lefeber +1

RA-L 2018

The control of mechatronic systems can often be enhanced if realtime information on the derivatives of a signal is available. These derivatives are not always measurable by sensors and should be estimated. Simple numerical derivatives cannot be applied, due to noise on the measured signals. Several

Cited by 8 Source ↗Scholar ↗

2016

Predicting Seat-Off and Detecting Start-of-Assistance Events for Assisting Sit-to-Stand With an Exoskeleton

Kevin Tanghe, Anna Harutyunyan, Erwin Aertbeliën, Friedl De Groote, Joris De Schutter, Peter Vrancx +1

RA-L 2016

Accurate and reliable event prediction is imperative for supporting movement with an exoskeleton. Two events are important during a sit-to-stand movement: seat-off, the event at which the subject leaves the chair and start-of-assistance for hip and knee, the earliest time at which assistance may be

Cited by 22 Source ↗Scholar ↗