Biologically inspired design framework for Robot in Dynamic Environments using Framsticks
This work addresses robot design challenges in automated industries, but it appears incremental as it builds on existing biological inspiration without clear broad advancements.
The authors tackled robot design complexity in dynamic environments by proposing a biologically inspired framework using co-evolution, virtual ecology, and lifetime learning, and tested it on a virtual Khepera robot in Framsticks to monitor behaviors and obtain parameters influencing hardware and software design.
Robot design complexity is increasing day by day especially in automated industries. In this paper we propose biologically inspired design framework for robots in dynamic world on the basis of Co-Evolution, Virtual Ecology, Life time learning which are derived from biological creatures. We have created a virtual khepera robot in Framsticks and tested its operational credibility in terms hardware and software components by applying the above suggested techniques. Monitoring complex and non complex behaviors in different environments and obtaining the parameters that influence software and hardware design of the robot that influence anticipated and unanticipated failures, control programs of robot generation are the major concerns of our techniques.