With the increased demand for customisation, developing task-specific robots for industrial and personal applications has become essential. Collaborative robots are often preferred over conventional industrial robots in human-centred production environments. However, fixed architecture robots lack the ability to adapt to changing user demands, while modular, reconfigurable robots provide a quick and affordable alternative. Standardised robot modules often derive their characteristics from conventional industrial robots, making them expensive and bulky and potentially limiting their wider adoption. To address this issue, the current work proposes a top-down multidisciplinary computational design strategy emphasising the low cost and lightweight attributes of modular robots within two consecutive optimisation problems. The first step employs an informed search strategy to explore the design space of robot modules to identify a low-cost robot architecture and controller. The second step employs dynamics-informed structural optimisation to reduce the robot’s net weight. The proposed methodology is demonstrated on a set of example requirements, illustrating that (1) the robot modules allow exploring non-intuitive robot architectures, (2) the structural mass of the resulting robot is 16 % lower compared to a robot designed using conventional aluminium tubes, and (3) the designed modules ensure the physical feasibility of the robots produced.