Evolutionary Developmental Robotics: Improving Morphology and Control of Physical Robots.

Evolutionary algorithms have previously been applied to the design of morphology and control of robots. The design space for such tasks can be very complex, which can prevent evolution from efficiently discovering fit solutions. In this article we introduce an evolutionary-developmental (evo-devo) experiment with real-world robots. It allows robots to grow their leg size to simulate ontogenetic morphological changes, and this is the first time that such an experiment has been performed in the physical world. To test diverse robot morphologies, robot legs of variable shapes were generated during the evolutionary process and autonomously built using additive fabrication. We present two cases with evo-devo experiments and one with evolution, and we hypothesize that the addition of a developmental stage can be used within robotics to improve performance. Moreover, our results show that a nonlinear system-environment interaction exists, which explains the nontrivial locomotion patterns observed. In the future, robots will be present in our daily lives, and this work introduces for the first time physical robots that evolve and grow while interacting with the environment.

Morphological Evolution of Physical Robots through Model-Free Phenotype Development.

Artificial evolution of physical systems is a stochastic optimization method in which physical machines are iteratively adapted to a target function. The key for a meaningful design optimization is the capability to build variations of physical machines through the course of the evolutionary process. The optimization in turn no longer relies on complex physics models that are prone to the reality gap, a mismatch between simulated and real-world behavior. We report model-free development and evaluation of phenotypes in the artificial evolution of physical systems, in which a mother robot autonomously designs and assembles locomotion agents. The locomotion agents are automatically placed in the testing environment and their locomotion behavior is analyzed in the real world. This feedback is used for the design of the next iteration. Through experiments with a total of 500 autonomously built locomotion agents, this article shows diversification of morphology and behavior of physical robots for the improvement of functionality with limited resources.

Mechanics and energetics in tool manufacture and use: a synthetic approach.

Tool manufacture and use are observed not only in humans but also in other animals such as mammals, birds and insects. Manufactured tools are used for biomechanical functions such as effective control of fluids and small solid objects and extension of reaching. These tools are passive and used with gravity and the animal users' own energy. From the perspective of evolutionary biology, manufactured tools are extended phenotypes of the genes of the animal and exhibit phenotypic plasticity. This incurs energetic cost of manufacture as compared to the case with a fixed tool. This paper studies mechanics and energetics aspects of tool manufacture and use in non-human beings. Firstly, it investigates possible mechanical mechanisms of the use of passive manufactured tools. Secondly, it formulates the energetic cost of manufacture and analyses when phenotypic plasticity benefits an animal tool maker and user. We take a synthetic approach and use a controlled physical model, i.e. a robot arm. The robot is capable of additively manufacturing scoop and gripper structures from thermoplastic adhesives to pick and place fluid and solid objects, mimicking primates and birds manufacturing tools for a similar function. We evaluate the effectiveness of tool use in pick-and-place and explain the mechanism for gripper tools picking up solid objects with a solid-mechanics model. We propose a way to formulate the energetic cost of tool manufacture that includes modes of addition and reshaping, and use it to analyse the case of scoop tools. Experiment results show that with a single motor trajectory, the robot was able to effectively pick and place water, rice grains, a pebble and a plastic box with a scoop tool or gripper tools that were manufactured by itself. They also show that by changing the dimension of scoop tools, the energetic cost of tool manufacture and use could be reduced. The work should also be interesting for engineers to design adaptive machines.

Active sensing system with in situ adjustable sensor morphology.

BACKGROUND: Despite the widespread use of sensors in engineering systems like robots and automation systems, the common paradigm is to have fixed sensor morphology tailored to fulfill a specific application. On the other hand, robotic systems are expected to operate in ever more uncertain environments. In order to cope with the challenge, it is worthy of note that biological systems show the importance of suitable sensor morphology and active sensing capability to handle different kinds of sensing tasks with particular requirements. METHODOLOGY: This paper presents a robotics active sensing system which is able to adjust its sensor morphology in situ in order to sense different physical quantities with desirable sensing characteristics. The approach taken is to use thermoplastic adhesive material, i.e. Hot Melt Adhesive (HMA). It will be shown that the thermoplastic and thermoadhesive nature of HMA enables the system to repeatedly fabricate, attach and detach mechanical structures with a variety of shape and size to the robot end effector for sensing purposes. Via active sensing capability, the robotic system utilizes the structure to physically probe an unknown target object with suitable motion and transduce the arising physical stimuli into information usable by a camera as its only built-in sensor. CONCLUSIONS/SIGNIFICANCE: The efficacy of the proposed system is verified based on two results. Firstly, it is confirmed that suitable sensor morphology and active sensing capability enables the system to sense different physical quantities, i.e. softness and temperature, with desirable sensing characteristics. Secondly, given tasks of discriminating two visually indistinguishable objects with respect to softness and temperature, it is confirmed that the proposed robotic system is able to autonomously accomplish them. The way the results motivate new research directions which focus on in situ adjustment of sensor morphology will also be discussed.