Robodimm: A Physics-Grounded Framework for Automated Actuator Sizing in Scalable Modular Robots

Actuator sizing is an early and consequential decision: joint torque and velocity specifications fix the motors, gearboxes and brakes before any CAD model exists. Sim4RAD is a MATLAB toolkit for that phase and for the verification that follows it. It builds a rigid-body model from a handful of parameters, and four analyses supply the specification: a static analysis combining lever-arm sampling with a posture search, giving a rated torque at a chosen payload envelope and a reproducible peak torque; a dynamics pipeline that reshapes a trajectory under one of four constraints, including the actuator torque-speed envelope; a stochastic analysis over many random motions, so a specification rests on a class of motions, not one trajectory; and a workspace and dexterity analysis that separates where the arm can reach from how it can reach there. Replacing the synthesized model by a URDF file turns the same analyses to verification. A 7-DOF anthropomorphic arm is compared in three layouts differing in the shoulder axis order and in whether the last wrist joint is coaxial with the payload. The static demand at half arm length is nearly the same in all three, and it sizes the joints rather than the sampled motion; reordering the shoulder axes leaves the worst-case torque unchanged at 55 N m and the reachable volume within 8 percent. A last wrist joint coaxial with the payload removes its gravity torque, reduces the adjacent wrist joint by almost a third and cuts the last joint demand tenfold in a 5 m/s scan, at the price of dexterity (mean 0.570 to 0.348). The same arm needs 20 to 37 times more torque for a 5 m/s target than for a 2 s motion: the scenario, not the trajectory, must be fixed first. Verification should use the URDF model of the detailed design; the toolkit is available at https://github.com/LasterLi/Sim4RAD.

There is a growing need for robots that can change their shape, size and mechanical properties to adapt to evolving tasks and environments. However, current shape-changing systems generally utilize bespoke, system-specific mechanisms that can be difficult to scale, reconfigure or translate from one application to another. This paper introduces a compact, easy-to-fabricate deployable actuator that achieves reversible scale and stiffness transformations through compound folding and zipping of flexible 3D-printed plastic strips into square-section deployable beams. The simple actuation method allows for smooth, continuous transitions between compact (flexible) and expanded (quasi-rigid) states, facilitating diverse shape and stiffness transformations when modules are combined into larger assemblies. The actuator's mechanical performance is characterized and an integrated system involving a four-module adaptive walking robot is demonstrated.

Different tasks performed by legged robots impose distinct torque and speed requirements on actuators. Existing robotic actuators are generally optimized at the component level for metrics such as torque or power density, without explicit task guidance. System-level optimization across components such as motors, gearboxes, and sensors is challenging because of the high computational cost and coupling among mechanical, electrical, and electromagnetic behaviors. Consequently, improvements in individual components may not translate into better robot performance in a specific task. To this end, we present a systematic optimization framework for task-oriented co-design of actuator hardware and control. First, surrogate models are employed to accelerate motor evaluation and support global exploration of the coupled design space. Then, a hierarchical mixed-variable optimization strategy is adopted, combining discrete enumeration with continuous search over dimensions and real-valued indices. These indices are rounded to select admissible values for the remaining discrete choices before each evaluation. Within this search, rated output torque density and task performance are jointly optimized, with Bezier-parameterized joint torque profiles determined for each hardware candidate. Finally, the effectiveness of the proposed framework is validated through actuator fabrication and experiments on a two-degree-of-freedom jumping leg. Based on its measured mass, the fabricated prototype achieves a nominal rated output torque density of 35.7 N m/kg, approximately 60% higher than that of a widely used commercial geared joint actuator, while being 18.6% lighter. Under matched bench conditions, it achieves 12.0% greater jump height at twice-rated torque. Together, these results demonstrate a systematic route from task requirements to actuator design and control.