Andrzej Buller

Automated evolutionary design, robustness, and adaptation of sidewinding locomotion of a simulated snake-like robot

Inspired by the efficient method of locomotion of the rattlesnake Crotalus cerastes, the objective of this work is automatic design through genetic programming (GP) of the fastest possible (sidewinding) locomotion of simulated limbless, wheelless snake-like robot (Snakebot). The realism of simulation is ensured by employing the Open Dynamics Engine (ODE), which facilitates implementation of all physical forces, resulting from the actuators, joints constrains, frictions, gravity, and collisions. Reduction of the search space of the GP is achieved by representation of Snakebot as a system comprising identical morphological segments and by automatic definition of code fragments, shared among (and expressing the correlation between) the evolved dynamics of the vertical and horizontal turning angles of the actuators of Snakebot. Empirically obtained results demonstrate the emergence of sidewinding locomotion from relatively simple motion patterns of morphological segments. Robustness of the sidewinding Snakebot, which is considered to be the ability to retain its velocity when situated in an unanticipated environment, is illustrated by the ease with which Snakebot overcomes various types of obstacles such as a pile of or burial under boxes, rugged terrain, and small walls. The ability of Snakebot to adapt to partial damage by gradually improving its velocity characteristics is discussed. Discovering compensatory locomotion traits, Snakebot recovers completely from single damage and recovers a major extent of its original velocity when more significant damage is inflicted. Exploring the opportunity for automatic design and adaptation of a simulated artifact, this work could be considered as a step toward building real Snakebots, which are able to perform robustly in difficult environments.

Evolution, Robustness, and Adaptation of Sidewinding Locomotion of Simulated Snake-Like Robot

Inspired by the efficient method of locomotion of the rattlesnake Crotalus cerastes, the objective of this work is automatic design through ge- netic programming, of the fastest possible (sidewinding) locomotion of simu- lated limbless, wheelless snake-like robot (Snakebot). The realism of simula- tion is ensured by employing the Open Dynamics Engine (ODE), which facili- tates implementation of all physical forces, resulting from the actuators, joints constrains, frictions, gravity, and collisions. Empirically obtained results dem- onstrate the emergence of sidewinding locomotion from relatively simple mo- tion patterns of morphological segments. Robustness of the sidewinding Snake- bot, considered as ability to retain its velocity when situated in unanticipated environment, is illustrated by the ease with which Snakebot overcomes various types of obstacles such as a pile of or burial under boxes, rugged terrain and small walls. The ability of Snakebot to adapt to partial damage by gradually improving its velocity characteristics is discussed. Discovering compensatory locomotion traits, Snakebot recovers completely from single damage and recov- ers a major extent of its original velocity when more significant damage is in- flicted. Contributing to the better understanding of sidewinding locomotion, this work could be considered as a step towards building real Snakebots, which are able to perform robustly in difficult environments.

Evolving Spike-Train Processors

The research described in this paper was motivated by the idea to process purposefully given spike-trains using a cellular automaton (CA). CAs have three attractive features, namely massive parallelism, locality of cellular interactions, and simplicity of basic components (cells). However, the difficulty of designing a CA for a specific behavior causes limited interest in this computational paradigm. Automating the design process would substantially enhance the viability of CAs. Evolving CAs for purposeful computation is a scientific challenge undertaken to date by, among others, Mitchell et al. [1], Sipper et al. [2] and de Garis et al. [3].

Evolutionary design, robustness and of sidewinding locomotion of simulated libmless wheelless robot [libmless read limbless]

The objective of this work is automatic design through genetic programming, of the fastest possible locomotion of simulated snake-like robot (Snakebot). The realism of simulation is ensured by employing the Open Dynamics Engine software library. Empirical results demonstrate the emergence of sidewinding as fastest locomotion gait. Robustness of the sidewinding is illustrated by the ease with which Snakebot overcomes various types of obstacles. The ability of Snakebot to adapt to partial damage by gradually improving its velocity characteristics is shown. Discovering compensatory locomotion traits, Snakebot recovers completely from single damage and recovers a major extent of its original velocity when more significant damage is inflicted.