Until today, in the field of motor learning and rehabilitation, haptic controllers were mostly limited to teach simple tasks such as movements along straight lines, curves, or circles. However, commonly, real-life tasks consist of more complex movements such as in writing, rehabilitation, or surgery. In this paper, a novel haptic controller for robot-assisted learning is introduced. This hybrid path controller can cope with interfering path sections, while it also incorporates the common requirements of effective motor learning: it allows freedom for making spatial errors, free timing to explore the task dynamics, and adaptation to the current skill level of the user. In a practicability study with two different robots, results confirmed the full functionality of the controller and its applicability for a broad range of complex movements.

The use of robots has attracted researchers to design numerous haptic training methods to support motor learning. However, investigations of new methods yielded inconclusive results regarding their effectiveness to enhance learning due to the diversity of tasks, haptic designs, participants skill level, and study protocols. In this review, we developed a taxonomy to identify generalizable findings out of publications on haptic training. In the taxonomy, we grouped the results of studies on healthy learners based on participants skill level and tasks characteristics. Our inspection of included studies revealed that: i) Performance-enhancing haptic methods were beneficial for novices, ii) Training with haptics was as effective as training with other feedback modalities, and iii) Performance-enhancing and performance-degrading haptic methods were useful for the learning of temporal and spatial aspects, respectively. We also observed that these findings are in line with results from robot-aided neurorehabilitation studies on patients. Our review suggests that haptic training can be effective to foster learning, especially when the information cannot be provided with other feedback modalities. We believe the findings from the taxonomy constitute a general guide, which can assist researchers when designing studies to investigate the effectiveness of haptics on learning different tasks.