TY - GEN
T1 - Independent Markov chain occupancy grid maps for representation of dynamic environment
AU - Saarinen, Jari
AU - Andreasson, Henrik
AU - Lilienthal, Achim J.
PY - 2012/1/1
Y1 - 2012/1/1
N2 - In this paper we propose a new grid based approach to model a dynamic environment. Each grid cell is assumed to be an independent Markov chain (iMac) with two states. The state transition parameters are learned online and modeled as two Poisson processes. As a result, our representation not only encodes the expected occupancy of the cell, but also models the expected dynamics within the cell. The paper also presents a strategy based on recency weighting to learn the model parameters from observations that is able to deal with non-stationary cell dynamics. Moreover, an interpretation of the model parameters with discussion about the convergence rates of the cells is presented. The proposed model is experimentally validated using offline data recorded with a Laser Guided Vehicle (LGV) system running in production use.
AB - In this paper we propose a new grid based approach to model a dynamic environment. Each grid cell is assumed to be an independent Markov chain (iMac) with two states. The state transition parameters are learned online and modeled as two Poisson processes. As a result, our representation not only encodes the expected occupancy of the cell, but also models the expected dynamics within the cell. The paper also presents a strategy based on recency weighting to learn the model parameters from observations that is able to deal with non-stationary cell dynamics. Moreover, an interpretation of the model parameters with discussion about the convergence rates of the cells is presented. The proposed model is experimentally validated using offline data recorded with a Laser Guided Vehicle (LGV) system running in production use.
UR - http://www.scopus.com/inward/record.url?scp=84872312765&partnerID=8YFLogxK
U2 - 10.1109/IROS.2012.6385629
DO - 10.1109/IROS.2012.6385629
M3 - Conference contribution
AN - SCOPUS:84872312765
SN - 9781467317375
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 3489
EP - 3495
BT - 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2012
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 25th IEEE/RSJ International Conference on Robotics and Intelligent Systems, IROS 2012
Y2 - 7 October 2012 through 12 October 2012
ER -