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Erik Berger

3 accepted papers

2019

Deep Learning of Proprioceptive Models for Robotic Force Estimation

IROS 2019poster

Many robotic tasks require fast and accurate force sensing capabilities to ensure adaptive behavior execution. While dedicated force-torque (FT) sensors are a common option, such devices induce extra costs, need additional power supply, and add weight to otherwise light-weight robotic systems. This…

Cited by 1SourceScholar
2016

Estimating perturbations from experience using neural networks and Information Transfer

IROS 2016poster

In order to ensure safe operation, robots must be able to reliably detect behavior perturbations that result from unexpected physical interactions with their environment and human co-workers. While some robots provide firmware force sensors that generate rough force estimates, more accurate force me…

Cited by 12SourceScholar
2016

Experience-based torque estimation for an industrial robot

ICRA 2016poster

Robotic manipulation tasks often require the control of forces and torques exerted on external objects. This paper presents a machine learning approach for estimating forces when no force sensors are present on the robot platform. In the training phase, the robot executes the desired manipulation ta…

Cited by 18SourceScholar