Robots as models of evolving systems

SignificanceWe present a fully realized adaptive resource landscape with diploid three-gene robots presenting interacting roles of population dynamics, mutations, breeding, death, and birth. Although modeling and theory serves as a guide here, the inherent complexity of our robobiology world makes it an experiment in exploring rules of Darwinian natural selection at a level difficult to simulate. We find that the lower the genetic diversity, the lower the survival probability of the robot population. We propose that diploid gene robots can act as avatars of diploid mammalian cells to explore novel programs of administration of drugs.

Deep Vision Servo Hand-Eye Coordination Planning Study for Sorting Robots

Within the context of large-scale symmetry, a study on deep vision servo hand-eye coordination planning for sorting robots was conducted according to the problems of low recognition-sorting accuracy and efficiency in existing sorting robots. In order to maintain the symmetry of the picking robot, a small telescopic sorting robot with RealSense depth vision servo embedded in the manipulator was developed. The workspace and posture of picking parcels were analyzed, and the coordinate transformation model of hand-eye coordination was established for the “Eye-in-hand” mode. The hand-eye coordinated sorting test shows that the average positioning accuracy of the end in the X, Y and Z directions is 3.49 mm, 2.76 mm and 3.32 mm respectively, and the average time is 19.19 s. Among them, the average time for the mechanical arm to pick up the package from the initial position is 12.02 s, the average time for intermediate identification and calculation is 3.79 s, and the average time for placing the package is 6.9 s. The time consumed by robot arm’s action accounts for 79.8% of the whole cycle. The robot structure and the hand-eye coordination strategy with RealSense depth vision servo embedded in the robot can meet picking operation requirements, and the design of a picking robot proposed in this paper can greatly improve the coordination symmetry of fruit target recognition, detection, and picking.

It doesn't always pay to be fit: success landscapes

Landscapes play an important role in many areas of biology, in which biological lives are deeply entangled. Here we discuss a form of landscape in evolutionary biology which takes into account (1) initial growth rates, (2) mutation rates, (3) resource consumption by organisms, and (4) cyclic changes in the resources with time. The long-term equilibrium number of surviving organisms as a function of these four parameters forms what we call a success landscape, a landscape we would claim is qualitatively different from fitness landscapes which commonly do not include mutations or resource consumption/changes in mapping genomes to the final number of survivors. Although our analysis is purely theoretical, we believe the results have possibly strong connections to how we might treat diseases such as cancer in the future with a deeper understanding of the interplay between resource degradation, mutation, and uncontrolled cell growth.