Learning Contact for Haptic Feedback: Switching X-lateral Teleoperators

In this paper, we propose X-lateral teleoperation: a novel hybrid unilateral-bilateral teleoperation framework. Bilateral teleoperation enables kinesthetic coupling between the operator and the remote environment with haptic feedback. However, in free motion, unlike unilateral teleoperators, bilateral teleoperators reflect undesirable operational forces to the operator. The proposed X-lateral teleoperation framework benefits from a learning-based contact detection algorithm which triggers switching from unilateral teleoperation in free motion to bilateral teleoperation in contact. We also present a neural network based two-class classification technique to detect contacts even with environments not seen in training. In experiments with linear motors and Phantom Omni devices, using sensorless force estimation, we show that the proposed method can decrease operational forces significantly over transparencyoptimized bilateral architectures.