The field of teleoperation with force telepresence has expanded its scope to include manipulation at different scales and in virtual worlds, and the key component of which is force feedback hand controller. This paper presents a novel force feedback hand controller system, including a 3-dof translational and 3-dof rotational hand controllers, respectively, to implement position and posture teleoperation of the robot end effector. The 3-dof translational hand controller adopts innovative three-axes decoupling structure based on the linear motor; the 3-dof rotational hand controller adopts serial mechanism based on three-axes intersecting at one point, improving its overall stiffness. Based on the kinematics, statics, and dynamics analyses for two platforms separately, the system applies big closed-loop force control method based on the zero force/torque, improving the feedback force/torque accuracy effectively. Experimental results show that self-developed 6-dof force feedback hand controller has good mechanical properties. The translational hand controller has the following advantages: simple kinematics solver, fast dynamic response, and better than 0.05？mm accuracy of three-axis end positioning, while the advantages of the rotational hand controller are wide turning space, larger than 1？Nm feedback, greater than 180 degrees of operating space of three axes, respectively, and high operation precision. 1. Introduction At present, the robot systems are widely used in hazardous operations, disaster, nuclear environment, deep sea, space, and other areas, which can replace humans in dangerous and extreme conditions to complete the tasks [1, 2]. When robots are working in special environment, the task usually requires high operating precision [3–5]. Due to the combination of human decision-making capacity and operational capability of robots in hazardous environment, teleoperation can complete complex and special tasks while making people away from the site [6, 7]. As an important interface used to build a close dynamic coupling between operators and robots, hand controller can send position, posture, and other information to the operation object. It can also accept the environmental information from control system, such as the force/torque, providing the operator with force telepresence and implementing effective interventions and control for robots [8]. In the teleoperation system, hand controller’s performance has a direct impact on the operating performance and reliability of the bilateral control system [9, 10]. According to the structure form, hand
References
[1]
R. J. Lian, “Adaptive self-organizing fuzzy sliding-mode radial basis-function neural-network controller for robotic systems,” IEEE Transactions on Industrial Electronics, vol. 64, no. 3, pp. 1493–1503, 2014.
[2]
S. H. Choi, I. B. Jeong, J. H. Kim, and J. J. Lee, “Context generator and behavior translator in a multilayer architecture for a modular development process of cyber-physical robot systems,” IEEE Transactions on Industrial Electronics, vol. 61, no. 2, pp. 882–892, 2014.
[3]
P. Hemakumara and S. Sukkarieh, “Learning UAV stability and control derivatives using gaussian processes,” IEEE Transactions on Robotics, vol. 29, no. 4, pp. 813–824, 2013.
[4]
Q. Chen, W. Chen, G. Yang, and R. Liu, “An integrated two-level self-calibration methodfor a cable-driven humanoid arm,” IEEE Transactions on Automation Science and Engineering, vol. 10, no. 2, pp. 380–391, 2013.
[5]
X. Gao, Q. Jia, H. Sun, and G. Chen, “Research on path planning for 7-DOF space manipulator to avoid obstacle based on A* algorithm,” Sensor Letters, vol. 9, no. 4, pp. 1515–1519, 2011.
[6]
P. Malysz and S. Sirouspour, “A kinematic control framework for single-slave asymmetric teleoperation systems,” IEEE Transactions on Robotics, vol. 27, no. 5, pp. 901–917, 2011.
[7]
X. Gao, H. Hu, Q. X. Jia, H. X. Sun, and J. Z. Song, “3D augmented reality teleoperated robot system based on dual vision,” Journal of China Universities of Posts and Telecommunications, vol. 18, no. 1, pp. 105–112, 2011.
[8]
S. K. Cho, H. Z. Jin, J. M. Lee, and B. Yao, “Teleoperation of a mobile robot using a force-reflection joystick with sensing mechanism of rotating magnetic field,” IEEE/ASME Transactions on Mechatronics, vol. 15, no. 1, pp. 17–26, 2010.
[9]
O. Linda and M. Manic, “Self-organizing fuzzy haptic teleoperation of mobile robot using sparse sonar data,” IEEE Transactions on Industrial Electronics, vol. 58, no. 8, pp. 3187–3195, 2011.
[10]
M. J. Fu and M. C. Cavusoglu, “Human-arm-and-hand-dynamic model with variability analyses for a stylus-based haptic interface,” IEEE Transactions on Systems, Man, and Cybernetics B: Cybernetics, vol. 42, no. 6, pp. 1633–1644, 2012.
[11]
I. Sarakoglou, N. Garcia-Hernandez, N. G. Tsagarakis, and D. G. Caldwell, “A high performance tactile feedback displayand its integration in teleoperation,” IEEE Transactions on Haptics, vol. 5, no. 3, pp. 252–263, 2012.
[12]
L. M. di Diodato, R. Mraz, S. N. Baker, and S. J. Graham, “A haptic force feedback device for virtual reality-fMRI experiments,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 15, no. 4, pp. 570–576, 2007.
[13]
J. Streque, A. Talbi, P. Pernod, and V. Preobrazhensky, “New magnetic microactuator design based on PDMS elastomer and MEMS technologies for tactile display,” IEEE Transactions on Haptics, vol. 3, no. 2, pp. 88–97, 2010.
[14]
J. Kim, P. H. Chang, and H.-S. Park, “Two-channel transparency-optimized control architectures in bilateral teleoperation with time delay,” IEEE Transactions on Control Systems Technology, vol. 21, no. 1, pp. 40–51, 2013.
[15]
H. Tanaka, K. Ohnishi, H. Nishi et al., “Implementation of bilateral control system based on acceleration control using FPGA for multi-DOF haptic endoscopic surgery robot,” IEEE Transactions on Industrial Electronics, vol. 56, no. 3, pp. 618–627, 2009.
[16]
A. Suzuki and K. Ohnishi, “Novel four-channel bilateral control design for haptic communication under time delay based on modal space analysis,” IEEE Transactions on Control Systems Technology, vol. 21, no. 3, pp. 882–890, 2013.
[17]
J. Wang and Y. Li, “Hybrid impedance control of a 3-DOF robotic arm used for rehabilitation treatment,” in Proceedings of the 6th annual IEEE Conference on Automation Science and Engineering, pp. 768–773, August 2010.
[18]
J. Wang and Y. Li, “A cooperated-robot arm used for rehabilitation treatment with hybrid impedance control method,” in Proceedings of the 3rd International Conference on Intelligent Robotics and Applications, no. 2, pp. 451–462, 2010.
