The goal of the experiments of the firt set is to test the basic properties of the system and to select values for the parameters used in the cost-based selection algorithm. Refer to section 5.1 of the paper for more details about the experiments.
Effect of noise and swarm size
The plots reported here highlight that the best was of partitioning the transportation task in terms of number of sub-tasks varies with the size of the swarm and with the noise on the odometry system of the robots. The plots report the results of experiments carried out in a 4.5 by 6.7 m arena, with a source-to-nest distance D of 4 meters (refer to Section 4 of the paper). The swarm size is selected in the set {4,6,8,10,15,20}. The odometry noise, expressed as percentage of the default noise, is selected in the set {0%, 20%, 50%, 100%, 120%}.
Effect of noise A first group of plots reports the median of the performance of the fixed algorithm for a given swam size and different values of noise. In general as the noise increases, the peak in performance is obtained in correspondance of a progressively diminishing value of the partition distance characterizing the fixed algorithm. In other words, the higher the noise, the smaller the distance traveled by a robot should be (i.e., the higher the number of sub-tasks the given task should be partitioned into).
Click on a link to open the corresponding plot:
4 robots6 robots 8 robots10 robots15 robots20 robots
Effect of the swarm size The following plots report the median of the performance of the fixed algorithm for a given noise factor and different swarm sizes. The plots highlight the effect of interference: for a given noise factor, the peak in performance is obtained, for increasing swarm sizes, by a progressively diminishing value of the partition distance characterizing the fixed algorithm. This indicates that in large swarms task partitioning is advantageous as it allows to physically separate the robots. Click on a link to open the corresponding plot:
No noise20% noise factor50% noise factorstandard noise120% noise factor
Effect of noise and swarmsize, boxplots The following plots report the same data, but plotted as notched boxplot. Each file plots the performance of the fixed partitioning algorithms for a given swarm size and level of noise. Click on a link to open the corresponding plot:
NOISE 0%
4 robots,
6 robots,
8 robots,
10 robots,
15 robots,
20 robots
NOISE 20%
4 robots,
6 robots,
8 robots,
10 robots,
15 robots,
20 robots
NOISE 50%
4 robots,
6 robots,
8 robots,
10 robots,
15 robots,
20 robots
NOISE 100%
4 robots,
6 robots,
8 robots,
10 robots,
15 robots,
20 robots
NOISE 120%
4 robots,
6 robots,
8 robots,
10 robots,
15 robots,
20 robots
TOP
Performance of the fixed algorithms
The following plot reports the performance of the fixed partitioning algorithms for different swarm sizes and values of the noise factor. The data reported is the same presented in the previous section (see
here), reported on the same plot for comparison. Click
here to open.
TOP