Abstract
Automatic grasp planning of robotic hand is always a difficult problem in robotics. Although researchers have developed underactuated hands with less degrees of freedom, automatic grasp planning is still a difficult problem because of the huge number of possible hand configurations. But humans simplify this problem by applying several usual grasp starting postures on most of grasp tasks. In this paper, a method for grasping planning is presented which can use a set of heuristic rules to limit the possibilities of hand configurations. By modeling the object as a set of primitive shapes and applying appropriate grasp starting postures on it, many grasp samples can be generated. And this is the basic content of the heuristic rules. Then, given grasp samples in finite number, a Simulink and Adams co-simulator is built to simulate these discrete grasp samples. The main purpose of the co-simulator is to simulate the dynamic behavior of robotic hand when grasping and measure the grasp quality using force closure and grasp measurement of largest-minimum resisted wrench. Last, a grasp library with force closure grasps is built where all items of grasp are sorted by the function value of grasp measurement. With the library, it’s easy to plan a grasp for certain object by just selecting an appropriate grasp from the library.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Khatib, O., Yokoi, K., Brock, O., et al.: Robots in human environments. In: 1999 IEEE International Workshop on Robot Motion and Control, Kiekrz, Poland, pp. 213–221. IEEE (1999)
Buss, M., Carton, D., Gonsior, B., et al.: Towards proactive human-robot interaction in human environments. In: 2011 IEEE International Conference on Cognitive Info Communications, Budapest, pp. 1–6. IEEE (2011)
Colombo, A., Fontanelli, D., Gandhi, D., et al.: Behavioural templates improve robot motion planning with social force posturel in human environments. In: 2013 IEEE Conference on Emerging Technologies & Factory Automation, Cagliari, Italy, pp. 1–6. IEEE (2013)
Oli, S., L’Esperance, B., Gupta, K.: Human motion behaviour aware planner (HMBAP) for path planning in dynamic human environments. In: 2013 IEEE International Conference on Advanced Robotics, Montevideo, Uruguay, pp. 1–7. IEEE (2013)
Alenya, G., Foix, S., Torras, C.: Using ToF and RGBD cameras for 3D robot perception and manipulation in human environments. Intel. Serv. Robot. 7(4), 211–220 (2014)
Xiong, C., Ding, H., Xiong, Y.: Fundamentals of Robotic Grasping and Fixturing, vol. 1, pp. 1–218. Springer, Heidelberg (2007)
Prattichizzo, D., Grasping, T.J.: Springer Handbook of Robotics, vol. 1, pp. 671–700. Springer, Heidelberg (2008)
Kragten, G., Baril, M., Gosselin, C., et al.: Stable precision grasps by underactuated grippers. IEEE Trans. Rob. 27(6), 1056–1066 (2011)
Bridgwater, L.B., Ihrke, C.A., Diftler, M.A., et al.: The Robonaut 2 hand - designed to do work with tools. In: IEEE International Conference on Robotics and Automation, pp. 3425–3430. IEEE (2012)
Markenscoff, X.: The geometry of grasping. Int. J. Rob. Res. 9(1), 61–74 (1990)
Salisbury, K., Roth, B.: Kinematic and force analysis of articulated hands. ASME J. Mech. Transm. Autom. Des. 105(1), 35–41 (1983)
Murray, R.M., Sastry, S.S., Li, Z.: A Mathematical Introduction to Robotic Manipulation. CRC Press Inc., Boca Raton (1994)
Zuo, B., Qian, W.: A force-closure test for soft multi-fingered grasps. Sci. China 41(1), 62–69 (1998)
Malvezzi, M., Prattichizzo, D.: Evaluation of grasp stiffness in underactuated compliant hands. In: IEEE International Conference on Robotics and Automation, pp. 2074–2079. IEEE (2013)
Zhu, X.-Y., Wang, J.: Synthesis of force-closure grasps on 3-D objects based on the Q distance. IEEE Trans. Robot. Autom. 19(4), 669–679 (2003)
Liu, Y.H.: Qualitative test and force optimization of 3-D frictional form-closure grasps using linear programming. IEEE Trans. Robot. Autom. 15(1), 163–173 (1999)
Tegin, J., Iliev, B., Skoglund, A., et al.: Real life grasping using an under-actuated robot hand simulation and experiments. In: 2009 IEEE International Conference on Advanced Robotics. Munich, Germany, pp. 1–8. IEEE (2009)
Li, S., Yao, S., Zhang, Y., et al.: Grasp planning analysis and strategy modeling for underactuated multi-fingered robot hand using in fruits grasping. Afr. J. Agric. Res. 6(9), 2086–2098 (2011)
Saxena, A., Driemeyer, J., Ng, A.: Robotic grasping of novel objects using vision. Int. J. Rob. Res. 27(2), 157–173 (2008)
Saxena, A., Chung, S., Ng, A.: 3-D depth reconstruction from a single still image. Int. J. Comput. Vis. 76(1), 53–69 (2008)
Lenz, I., Lee, H., Saxena, A.: Deep learning for detecting robotic grasps. Int. J. Robot. Res. 34(4–5), 705–724 (2014)
Yu, Z., Qian, W.: Linearizing the soft finger contact constraint with application to dynamic force distribution in multifingered grasping. Sci. China 48(2), 121–130 (2005)
Acknowledgement
The authors would like to acknowledge the National Natural Science Foundation of China (61733001, 61573063, 61503029, U1713215) for its support and funding of this paper.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Wang, W., Zhang, Q., Sun, Z., Chen, X., Jiang, Z. (2019). Automatic Operating Method of Robot Dexterous Multi-fingered Hand Using Heuristic Rules. In: Sun, F., Liu, H., Hu, D. (eds) Cognitive Systems and Signal Processing. ICCSIP 2018. Communications in Computer and Information Science, vol 1005. Springer, Singapore. https://doi.org/10.1007/978-981-13-7983-3_37
Download citation
DOI: https://doi.org/10.1007/978-981-13-7983-3_37
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-7982-6
Online ISBN: 978-981-13-7983-3
eBook Packages: Computer ScienceComputer Science (R0)