H. D. Taghirad — accepted AI-conference papers

2024

A Graph-Based Self-Calibration Technique for Cable-Driven Robots with Sagging Cable

M. R. Dindarloo, A. S. Mirjalili, S. A. Khalilpour, R. Khorrambakht, Stephan Weiss, H. D. Taghirad

IROS 2024poster

The efficient operation of large-scale Cable-Driven Parallel Robots (CDPRs) relies on precise calibration of kinematic parameters and the simplicity of the calibration process. This paper presents a graph-based self-calibration framework that explicitly addresses cable sag effects and facilitates th…

Cited by 0 Source ↗Scholar ↗

2022

An Observer-Based Responsive Variable Impedance Control for Dual-User Haptic Training System

A. Rashvand, R. Heidari, M. Motaharifar, A. Hassani, M.R. Dindarloo, M. J. Ahmadi +3

IROS 2022poster

This paper proposes a variable impedance control architecture to facilitate eye surgery training in a dual-user haptic system. In this system, an expert surgeon (the trainer) and a novice surgeon (the trainee) collaborate on a surgical procedure using their own haptic devices. The mechanical impedan…

Cited by 3 Source ↗Scholar ↗