Real-world evolution adapts robot morphology and control to hardware limitations

Abstract

For robots to handle the numerous factors that can affect them in the real world, they must adapt to changes and unexpected events. Evolutionary robotics tries to solve some of these issues by automatically optimizing a robot for a specific environment. Most of the research in this field, however, uses simplified representations of the robotic system in software simulations. The large gap between performance in simulation and the real world makes it challenging to transfer the resulting robots to the real world. In this paper, we apply real world multi-objective evolutionary optimization to optimize both control and morphology of a four-legged mammal-inspired robot. We change the supply voltage of the system, reducing the available torque and speed of all joints, and study how this affects both the fitness, as well as the morphology and control of the solutions. In addition to demonstrating that this realworld evolutionary scheme for morphology and control is indeed feasible with relatively few evaluations, we show that evolution under the different hardware limitations results in comparable performance for low and moderate speeds, and that the search achieves this by adapting both the control and the morphology of the robot.

Data-efficient Learning of Morphology and Controller for a Microrobot

“…Our work is related to efforts to optimize controls for robots with non-fixed or reconfigurable morphologies [11], [12], [13], [14], [15], where the controller must handle changes in the robot's physical configuration, either to cope with unanticipated damage [13], [14] or prepare for different tasks [15]. Notably, [16] jointly evolve both morphological and gait parameters on a physical robot able to change its leg lengths dynamically. Application of this method is restricted to robots able to rapidly, repeatedly, and precisely alter their own morphology.…”

Self-Modifying Morphology Experiments with DyRET: Dynamic Robot for Embodied Testing

“…We hand designed parameters for a conservative gait (referred to as "base gait") based on experience from previous experiments [18], [23]. The walking speed of the robot is limited by the maximum rotational speed of the servos.…”

“…There are also examples of self-reconfiguring morphology used exclusively to guide the search for a better controller of a single hand-designed optimal morphology [17]. In our previous work, we have demonstrated in that earlier versions of the DyRET platform, presented in this paper, can be used 470mm 270mm for evolutionary experiments to optimize morphology using mechanical self-reconfiguration [18]. Our work was the first example of such an approach as far as we are aware.…”

Evolving Robots on Easy Mode: Towards a Variable Complexity Controller for Quadrupeds

“…For this investigation, we have selected a range of different evaluation budgets to test. We have previously used 64 and 128 evaluations in our hardware experiments [14,2], and 512, 2048 and 8192 evaluations gives a range more appropriate for simulation experiments. Fig.…”