Improved grid mapping technology based on Rao-Blackwellized particle filters and the gradient descent algorithm

References

• Arif, T. E., & Ali, O. E. (2015). Fusing inertial sensor data in an extended Kalman filter for 3D camera tracking. IEEE Transactions on Image Processing, 24(2), 538–548. doi: 10.1109/TIP.2014.2380176
   PubMed Web of Science ®Google Scholar
• Doucet, A., Freitas, N. D., Murphy, K. P., & Russel, S. J. (2013). Rao-Blackwellised particle filtering for dynamic Bayesian networks. Statistics, 176–183.
   Google Scholar
• Florian, H., Nico, K., Jeff, O., & Darius, B. (2010). Efficient occupancy grid computation on the GPU with lidar and radar for road boundary detection. Pages 1006–1013, 21-24 June.
   Google Scholar
• Fourati, H., Manamanni, N., Afilal, L., & Handrich, Y. (2013, July 17-19). Position Estimation approach by complementary filter-aided IMU for indoor environment. 2013 European control conference (pp. 4208–4213).
   Google Scholar
• Georg, T., & Dirk, W. (2017). Evidential grid-based tracking and mapping. IEEE Transactions on Intelligent Transportation Systems, 6(18), 1454–1466.
   Google Scholar
• Giorgio, G., Cyrill, S., & Wolfram, B. (2007). Improved techniques for grid mapping with Rao-Blackwellized particle filters. IEEE Transactions on Robotics, 23(1), 34–46. doi: 10.1109/TRO.2006.889486
   Web of Science ®Google Scholar
• Havangi, R., Taghirad, H. D., Nekoui, M. A., & Teshnehlab, M. (2014). A square root unscented FastSLAM with improved proposal distribution and resampling. IEEE Transactions on Industrial Electronics, 61(5), 2334–2345. doi: 10.1109/TIE.2013.2270211
   Web of Science ®Google Scholar
• Kallapur, A., Petersen, I., & Anavatti, S. (2009). A robust gyroless attitude estimation scheme for a small fixed-wing unmanned aerial vehicle. Asian Control Conference, 666–671.
   Google Scholar
• Lee, H. C., Lee, S. H., Choi, M. H., & Lee, B. H. (2012). Probabilistic map merging for multi-robot RBPF-SLAM with unknown initial poses. Robotica, 30(2), 205–220. doi: 10.1017/S026357471100049X
   Google Scholar
• Lee, J. S., Sang, Y. N., & Wan, K. C. (2011). Robust RBPF-SLAM for indoor mobile Robots using sonar sensors in non-static environments. Advanced Robotics, 25(9–10), 1227–1248. doi: 10.1163/016918611X574696
   Web of Science ®Google Scholar
• Madgwick, S. O. H. (2010). An efficient orientation filter for inertial and inertial/magnetic sensor arrays. ResearchGate.
   Google Scholar
• Madgwick, S. O. H., Harrison, A. J. L., & Vaidyanathan, R. (2011). Estimation of IMU and MARG orientation using a gradient descent algorithm. IEEE international conference on rehabilitation robotics 2011, 5975346.
   Google Scholar
• Matthias, S., Volker, W., & Jürgen, A. (2014, May 31-June 7). Grid mapping in dynamic road environments: Classification of dynamic cell hypothesis via tracking. 2014 IEEE International Conference on Robotics and Automation (pp. 3995–4002).
   Google Scholar
• Predrag, S. S., & Marko, B. M. (2010). Accelerated gradient descent methods with line search. Numerical Algorithms, 54(4), 503–520. doi: 10.1007/s11075-009-9350-8
   Web of Science ®Google Scholar
• Sebastian, O. H. M., Andrew, J. L. H., & Ravi, V. (2011, June 29-July 1). Estimation of IMU and MARG orientation using a gradient descent algorithm. 2011 IEEE International Conference on Rehabilitation Robotics.
   Google Scholar
• Soltero, D. E., Schwager, M., & Rus, D. (2014). Decentralized path planning for coverage tasks using gradient descent adaptive control. The International Journal of Robotics Research, 33(3), 401–425. doi: 10.1177/0278364913497241
   Web of Science ®Google Scholar
• Thrun, S. (2001). A probabilistic online mapping algorithm for teams of mobile robots. The International Journal of Robotics Research, 20(20), 335–363. doi: 10.1177/02783640122067435
   Google Scholar
• Yang, J. D., Yang, J. H., & Cai, Z. S. (2015). An efficient approach to pose tracking based on odometric error modelling for mobile robots. Robotica, 33(6), 1231–1249. doi: 10.1017/S0263574714000654
   Web of Science ®Google Scholar