Tham khảo tài liệu 'field and service robotics - corke p. and sukkarieh s.(eds) part 8', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Constrained Motion Planning in Discrete State Spaces 277 It is important to observe that these issues are primarily relevant for local planning. When the distance to goal is much larger than the minimum turning radius of the vehicle the under-estimation error percentage of Euclidean distance will become small thus making this metric a viable heuristic option. We this in mind we propose a hybrid approach to calculating the heuristic in the close vicinity of the robot a local estimation procedure that considers the vehicle s kinematic model is used whereas in the far range Euclidean distance is sufficiently accurate. Based on experimental studies we found that a good threshold for switching between local and global heuristics is 10 minimum turning radii. As we mentioned it is crucial for the heuristic to be as accurate as possible for high efficiency. However there is no known closed-form solution for calculating the local heuristic and obtaining an accurate estimate requires solving the original planning problem. Thus we defined an off-line pre-processing step to create the heuristic look-up table LUT . The table is simply a compilation of the costs to travel from the origin to all lattice nodes in its local neighborhood. These costs are determined by running the planner for each possible path endpoints using simply Euclidean distance as heuristic which is guaranteed to be an under-estimate. LUT generation could be a lengthy process but it is performed off-line and the agenda for future work includes developing advanced function approximators to eliminate this pre-processing. The exact values for the path costs provided by the LUT result in the dramatic speed-up of the planner as described in the next section. Path Planner Results In order to quantify the performance of the present path planner we undertook a simulation study that included performing a statistically significant number of planning experiments where initial and final path configurations were .
