Passive Walking

Going on with robots, in the last talk we presented another interesting paper, this time written by Tad McGeer:

«Passive walking with knees»

This is about the role of knees in passive dynamic walking bipeds. It is  shown that giving just a slope, gravity energy is sufficient to keep walking down a pair of legs. With no other motor input, the machine will settle into natural gait. This evidences that morphological computation is implicit in natural locomotion systems. In this sense, this paper has originated new contoller systems in which the CoT (Coefficient of Transportation) could be optimized getting it near to the human one (of 0.2 vs 3.27 of Asimo robot by Honda). Furthermore, also prosthetics field could benefit from these new controllers and maybe evolutionary computation has new roles and goals to accomplish, but that is just another research issue.

Environment-driven evolution in robot swarms

In the last Friday paper seminar we were discussing the paper:

• Environment-Driven Embodied Evolution in a Population of Autonomous Agents by Nicolas Bredeche and Jean-Marc Montanier

which was presented at PPSN XI where we were attending as we mentioned.

Authors present a nice work on  swarm robotics where they try to evolve robot controllers using a fixed size population of autonomous robots. Evolution will take place in a decentralized fashion where no information on a possibly changing environment is provided. In that context, evolution is challenged to react to changes on-line and self-adapt to the environment without the global knowledge  on the problem that the fitness function would provide. That way «fitness» is implicit within the environment and the success criterion of a given strategy is defined as follows: one specific strategy is successful if it manages to spread over the population.

To that aim, authors propose mEDEA (minimal Environment-driven Distributed Evolutionary Adaptation), an intuitive algorithm which tackle the problem and tries to evolve controllers following a simple but elegant rule: those robot controllers that maximize the number of matings while preventing running out of energy will succeed on spreading their genomes.