Recent advancements in constrained kinematic control make it an attractive
strategy for controlling robots with arbitrary geometry in challenging tasks.
Most current works assume that the robot kinematic model is precise enough for
the task at hand. However, with increasing demands and safety requirements in
robotic applications, there is a need for a controller that compensates online
for kinematic inaccuracies. We propose an adaptive constrained kinematic
control strategy based on quadratic programming, which uses partial or complete
task-space measurements to compensate online for calibration errors. Our method
is validated in experiments that show increased accuracy and safety compared to
a state-of-the-art kinematic control strategy.Comment: Accepted on T-RO 2022, 16 Pages. Corrected a few typos and adjusted
figure placemen