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2011 | 21 | 2 | 363-377

Tytuł artykułu

Supporting locomotive functions of a six-legged walking robot

Treść / Zawartość

Warianty tytułu

Języki publikacji

EN

Abstrakty

EN
This paper presents a method for building a foothold selection module as well as methods for the stability check for a multi-legged walking robot. The foothold selection decision maker is shaped automatically, without expert knowledge. The robot learns how to select appropriate footholds by walking on rough terrain or by testing ground primitives. The gathered knowledge is then used to find a relation between slippages and the obtained local shape of the terrain, which is further employed to assess potential footholds. A new approach to function approximation is proposed. It uses the leastsquares fitting method, the Kolmogorov theorem and population-based optimization algorithms. A strategy for re-learning is proposed. The role of the decision support unit in the control system of the robot is presented. The importance of the stability check procedure is shown. A method of finding the stability region is described. Further improvements in the stability check procedure due to taking into account kinematic correction are reported. A description of the system for calculating static stability on-line is given. Methods for measuring stance forces are described. The measurement of stance forces facilitates the extended stability check procedure. The correctness of the method is proved by results obtained in a real environment on a real robot.

Rocznik

Tom

21

Numer

2

Strony

363-377

Opis fizyczny

Daty

wydano
2011
otrzymano
2010-01-15
poprawiono
2010-06-22
poprawiono
2010-11-16

Twórcy

  • Institute of Control and Information Engineering, Poznań University of Technology, ul. Piotrowo 3A, 60-965 Poznań, Poland
  • Institute of Control and Information Engineering, Poznań University of Technology, ul. Piotrowo 3A, 60-965 Poznań, Poland

Bibliografia

  • Annunziato, M. and Pizzuti, S. (2000). Adaptive parameterization of evolutionary algorithms driven by reproduction and competition, Proceedings of ESIT 2000, Aachen, Germany, Vol. 1, pp. 31-35.
  • Bai, S. and Low, K.H. (2001). Terrain evaluation and its application to path planning for walking machines, Advanced Robotics 15(1): 729-748.
  • Bai, S., Low, K.H. and Zielińska, T. (1999). A new free gait generation for quadrupeds based on primary/secondary gait, Proceedings of the IEEE International Conference on Robotics and Automation, Detroit, MI, USA, pp. 1371-1376.
  • Barghava, S. and Waldron, K. (1988). Stability analysis of the walking beam vehicle, Proceedings of the International Advanced Robotics Conference, Pisa, Italy, pp. 114-119.
  • Belter, D. (2009). Adaptive foothold selection for a hexapod robot walking on rough terrain, 7th Workshop on Advanced Control and Diagnosis, Zielona Góra, Poland, (on CDROM).
  • Belter, D., Kasiński, A. and Skrzypczyński, P. (2008). Evolving feasible gaits for a hexapod robot by reducing the space of possible solutions, Proceedings of the IEEE International Conference on Intelligent Robots and Systems, Nice, France, pp. 2673-2678.
  • Belter, D. and Skrzypczyński, P. (2009). Efficient gait learning in simulation: Crossing the reality gap by evolutionary model identification, in O. Tosun, H.L. Akin, M.O. Tokhi and G.S.Virk (Eds.), Mobile Robotics: Solutions and Challenges, World Scientific, Singapore, pp. 861-868.
  • Belter, D., Walas, K. and Kasiński, A. (2008). Distributed control system of DC servomotors for six legged walking robot, Proceedings of the International Power Electronics and Motion Control Conference, EPE-PEMC 2008, Poznań, Poland, pp. 1044-1049.
  • Bretl, T. and Lall, S. (2006). A fast and adaptive test of static equilibrium for legged robots, Proceedings of the International Robotics and Automation Conference, Orlando, FL, USA, pp. 1109-1116.
  • Bretl, T. and Lall, S. (2008). Testing static equilibrium for legged robots, IEEE Transactions on Robotics 24(4): 794-807, DOI: 10.1109/TRO.2008.2001360.
  • Burnhamn, K. and Anderson, D. (2002). Model Selection and Multimodel Inference: A Practical InformationTheoretical Approach, Springer-Verlag, New York, NY.
  • Dahlquist, G. and Bjorck, A. (1974). Numerical Methods, Prentice Hall, Englewood Cliffs, NJ.
  • Gassmann, B., Frommberger, L., Dillmann, R. and Berns, K. (2003). Real-time 3d map building for local navigation of a walking robot in unstructured terrain, Proceedings of the IEEE International Conference on Intelligent Robots and Systems, Las Vegas, NV, USA, pp. 2185-2190.
  • Gonzalez, P., Estremera, J., Garcia, E. and Armada, M. (2005). Force distribution in closed kinematic chains, Autonomous Robots 18(1): 43-57, DOI: 10.1023/B:AURO.0000047288.23401.5c.
  • Gutmann, J.-S., Fukuchi, M. and Fujita, M. (2004). Stairclimbing control of humanoid robot using force and accelerometer sensors, Proceedings of the International Intelligent Robots and Systems Conference, Sendai, Japan, pp. 1407-1413.
  • Kalakrishnan, M., Buchli, J., Pastor, P. and Schaal, S. (2009). Learning locomotion over rough terrain using terrain templates, Proceedings of the IEEE International Conference on Intelligent Robots and Systems, St. Louis, MO, USA, pp. 167-172.
  • Kennedy, J. and Eberhart, R. (1995). Particle swarm optimization, Proceedings of the IEEE International Conference on Neural Networks, Piscataway, Australia, pp. 1942-1948.
  • Kolmogorov, A. (1957). On the representation of continous function of several variables by superpositions of continous functions of one variable and addition, Doklady Akademii Nauk SSSR 114(4): 953-956.
  • Kolter, J., Rodgers, M. and Ng, A. (2008). A control architecture for quadruped locomotion over rough terrain, Proceedings of the IEEE International Conference on Robotics and Automation, Pasadena, CA, USA, pp. 811-818.
  • Kolter, J., Youngjun, K. and Ng, A. (2009). Stereo vision and terrain modeling for quadruped robots, Proceedings of the IEEE International Conference on Robotics and Automation, Kobe, Japan, pp. 1557-1564.
  • Kosiński, W. and Weigl, M. (1998). General mapping approximation problems solving by neural networks and fuzzy inference systems, Systems Analysis Modelling Simulation 30(1): 11-28.
  • Kumar, V. and Waldron, K. (1988). Force distribution in closed kinematic chains, Proceedings of the International Robotics and Automation Conference, Philadelphia, PA, USA, pp. 114-119.
  • Łabecki, P., Łopatowski, A. and Skrzypczyński, P. (2009). Terrain perception for a walking robot with a low-cost structured light sensor, Proceedings of the 4th European Conference on Moblie Robots, Dubrovnik, Croatia, pp. 199-204.
  • Li, T.-H., Su, Y.-T., Kuo, C.-H., Chen, C.-Y., Hsu, C.-L. and Lu, M.-F. (2007). Stair-climbing control of humanoid robot using force and accelerometer sensors, Proceedings of the SICE Annual Conference, Takamatsu, Japan, pp. 2115-2120.
  • Lobo, M., Vandenberghe, L., S.Boyd and Lebret, H. (1998). Applications of second-order cone programming, Linear Algebra and Its Applications 284(1-3): 193-228, DOI: 10.1016/S0024-3795(98)10032-0.
  • Lorentz, G. (1986). Approximation of Functions, American Mathematical Society, New York, NY.
  • Rebula, J., Neuhaus, P., Bonnlander, B., Johnson, M. and Pratt, J. (2007). A controller for the littledog quadruped walking on rough terrain, Proceedings of the IEEE International Conference on Robotics and Automation, Roma, Italy, pp. 1467-1473.
  • Roennau, A., Kerscher, T., Ziegenmeyer, M., Zoellner, J. and Dillmann, R. (2009). Six-legged walking in rough terrain based on foot point planning, in O. Tosun, H.L. Akin, M.O. Tokhi and G.S. Virk (Eds.) Mobile Robotics: Solutions and Challenges, World Scientific, Singapore, pp. 591-698.
  • Schmucker, U., Schneider, A. and Rusin, V. (2003). Interactive Virtual Simulator (IVS) of six-legged robot Katharina, Proceedings of the IEEE International Conference on Climbing and Walking Robots, Catania, Italy, pp. 327-332.
  • Smith, R. (2007). Open dynamics engine, www.ode.org.
  • Vernaza, P., Likhachev, M., Bhattacharya, S., Chitta, S. and Kushleyev, A. Lee, D. (2009). Search-based planning for a legged robot over rough terrain, Proceedings of the IEEE International Conference on Robotics and Automation, Kobe, Japan, pp. 2380-2387.
  • Walas, K. (2009). Static equilibrium condition for a multi-leg, stairs climbing walking robot, in K.R. Kozlowski (Ed.), Robot Motion and Control 2009, Lecture Notes in Control and Information Sciences, Vol. 396, Springer-Verlag, Berlin/Heidelberg, pp. 197-206, DOI: 10.1007/978-1-84882985-5.
  • Walas, K., Belter, D. and Kasiński, A. (2008). Control and environment sensing system for a six-legged robot, Journal of Automation, Mobile Robotics & Intelligent Systems 2(3): 26-31.
  • Zhou, D., Low, K. and Zielińska, T. (2000). An efficient footforce distribution algorithm for quadruped walking robots, Robotica 18(4): 403-413.

Typ dokumentu

Bibliografia

Identyfikatory

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bwmeta1.element.bwnjournal-article-amcv21i2p363bwm
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