tailieunhanh - Multiagent-Systems 2010 Part 12

Tham khảo tài liệu 'multiagent-systems 2010 part 12', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Effective Multi-Model Motion Tracking Under Multiple Team Member Actuators 323 DBN representation Following the play-based motion model we can use dynamic Bayesian networks DBNs to represent the whole system for team member and ball tracking in a natural and compact way as shown in Figure 4 and Figure 5 respectively. In the two graphs the system state is represented by variables play P tactic T infrared sensor measurement s ball state x ball motion model index m vision sensor measurement of ball z team member state x team member motion model index m vision sensor measurement of team member z where each variable takes on values in some space. The variables change over time in discrete intervals so that . xt is the ball state at time t. Furthermore the edges indicate dependencies between the variables. For instance in Figure 5 the ball motion model index mt depends on mt-1 Tt-1 T t-1 st and xt-1 hence there are edges coming from the latter five variables to mt. For the rest of this section we give the balltracking algorithm following Figure 5. The team-member-tracking algorithm can be obtained similarly following Figure 4. Fig. 4. A dynamic Bayesian network for team member tracking. Filled circles represent deterministic variables with are observable or are known as tactics or plays that the robot is executing. Importance sampling function We use the sequential Monte Carlo method to track the motion model m and the multitarget state x. Particle filtering is a general purpose Monte Carlo scheme for tracking in a dynamic system Doucet et al. 2001 . It maintains the belief state at time t as a set of particles p 1 pt2 ptNs where each p i is a full instantiation of the tracked variables 324 Multiagent Systems pt w wti is the weight of particle p l and Ns is the number of particles. In our case P l 1 1 . to I . . 1 V T ol i nn TV . . o T o vl i i1 OT T o vl i 1 T T t 0 i It i T t t m .ỉoiiidkeouriiuiaiiuiiiiiure c iicreLe i t VvX .