This plot compares the market size and growth for top 7 global markets for robotics products and services. The data comes from a leading market research company with a focus on emerging technologies. The plot shows parent markets and corresponding segments.
A summary of the market data used for the plot (parent market level):
kable(data_vis)
| market_name | number_of_segments | total_size_USDM | avg_growth_rate_YoY_pct |
|---|---|---|---|
| Global Agricultural Robots Market | 5 | 3974.95 | 45.84 |
| Global Collaborative Robots Market | 5 | 2146.10 | 64.30 |
| Global Industrial Robot Sensors Market | 9 | 8403.24 | 7.39 |
| Global Industrial Robot Vision Systems Market | 5 | 2391.75 | 10.10 |
| Global Professional Cleaning Robots Market | 6 | 105.93 | 58.05 |
| Global Robotics as a Service Market | 6 | 971.57 | 19.65 |
| Global Vision Guided Robotics Market | 6 | 7970.00 | 16.42 |
The plot was developed using R’s ggplot2 package, and it combines barplots and scatter plots arranged in a polar coordinate system. Below is the R code:
ggplot(data_to_plot, aes(x = as.factor(id), y = mean_size, fill = market_name)) +
geom_hline(yintercept = my_y_axis[4], colour = "grey", size = .15) +
geom_hline(yintercept = my_y_axis[3], colour = "grey", size = .15) +
geom_hline(yintercept = my_y_axis[2], colour = "grey", size = .15) +
geom_hline(yintercept = my_y_axis[1], colour = "grey", size = .15) +
geom_hline(yintercept = 0, colour = "grey", size = .15) +
geom_bar(aes(x = as.factor(id), y = mean_size, fill = market_name), stat = "identity", width = 0.6) + #market size
geom_point(aes(x = as.factor(id), y = mean_growth/30, fill = market_name), colour = "grey30", shape = 21, size = 2, stroke = .75) + #market growth
scale_y_continuous(limits = c(0,10), sec.axis = sec_axis(trans = ~.*30)) +
annotate("text", x = rep(max(data_to_plot$id),4), y = my_y_axis, label = paste0("$", as.character(my_y_axis), "B|", as.character(my_y_axis_sec), "%"), color="grey55", size = 2.5 , angle = 0, fontface="bold", hjust=0.5) +
ylim(-5, 5) +
theme_minimal() +
theme(
legend.position = "none",
axis.text = element_blank(),
axis.title = element_blank(),
plot.title = element_text(hjust = 0.5),
panel.grid = element_blank(),
plot.margin = unit(c(-3,-3,-6,-3), "cm")) +
coord_polar() +
geom_text(data = label_data, aes(x = id, y = 0.1, label = market_segment_name, hjust = hjust), color = "grey25", fontface = "bold", size = 2.75, angle = label_data$angle, inherit.aes = F) + #market segment labels
geom_segment(data=base_data, aes(x = start, y = -0.25, xend = end, yend = -.25), colour = "black", alpha=0.8, size=0.7 , inherit.aes = FALSE ) +
geom_text(data = base_data, aes(x = title, y = -1.3, label = market_name, colour = market_name), size = 3.25, fontface = "bold", inherit.aes = F) + #market label
geom_text(x = 0, y = 5, label = "Top largest and fastest growing market segments for robotics products and services", size = 6) + #title
geom_text(x = 0, y = 4.25, label = "Average for 2020-22 period. Bars represent market size in US$ Billion. Dots represent year-over-year percentage growth.", size = 3.75) #subtitle
The plot help us see that, although the Industrial Robot Sensors and the Vision Guided Robotics markets are the largest markets currently, they are not expected to grow substantially in the coming years. Rather, we expect to see a significant growth in Collaborative Robots, Professional Cleaning Robots and Agricultural Robots markets in the coming years. This suggests a shift from the use of robotics in industrial settings characterised by repetitive tasks, to the use of robotics in collaborative, commercial and outdoor environments characterised by unstructured, dynamic tasks, a trend likely to be stimulated by recent developments in machine learning and robot dexterity.