Poor trunk posture, especially during long periods of sitting, could lead to many issues such as Low Back Pain (LBP) and Forward Head Posture (FHP). Typical solutions are based on visual or vibration-based feedback. However, these feedback systems could lead to feedback being ignored by user and phantom vibration syndrome, respectively. Moreover, trunk posture needs to be corrected during rehabilitation of stroke patients to reduce trunk compensation. Proposed solutions in the literature to reduce trunk compensation primarily include strapping patients to the chair, which has several disadvantages. In this study, we propose using augmented haptic feedback for postural adaptation. In this two-part study, twenty-four healthy participants (age 25.87 ± 2.17 years) adapted to three different postural targets in the anterior direction while performing a unimanual reaching task using a robotic device. Results suggest a strong adaptation to the desired postural targets. Mean anterior trunk bending after intervention is significantly different as compared to baseline measurements for all postural targets. Additional analysis of movement straightness and smoothness indicates an absence of any negative interference of posture-based feedback on the performance of reaching movement. Taken together, these results suggest that augmented haptic feedback-based system could be used for postural adaptation applications.