在一些进化机器人实验中,进化的机器人从模拟转移到现实,而传感器/电机数据从现实中流回,以改善下一次传输。我们设想了这种方法的推广:模拟到现实的管道。在这个管道中,越来越具体的代理流过一系列越来越真实的物理模拟器,而数据向下流动以改善相邻模拟器之间的下一次传输;物理现实是该链中的最后一个环节。作为第一个概念证明,我们引入了一个两环节链:一个快速但低保真度(lo-fi)模拟器托管最低限度体现的代理,逐渐发展控制器和形态,以定居缓慢但高保真(hi-fi)模拟器。因此,药剂是物理支架。我们在这里表明,给定相同的计算预算,这些物理脚手架机器人在高保真模拟器中的性能比仅在高保真模拟器中进化的机器人高,但只针对足够困难的任务。这些结果表明,模拟到现实的管道可能会在模拟中加速演化,而在现实中锚定结果之间取得良好的平衡。使调查员不必预先指定机器人的形态,并为可扩展铺平道路,自动化,机器人生成系统。
In some evolutionary robotics experiments, evolved robots are transferred from simulation to reality, while sensor/motor data flows back from reality to improve the next transferral. We envision a generalization of this approach: a simulation-to-reality pipeline. In this pipeline, increasingly embodied agents flow up through a sequence of increasingly physically realistic simulators, while data flows back down to improve the next transferral between neighboring simulators; physical reality is the last link in this chain. As a first proof of concept, we introduce a two-link chain: A fast yet low-fidelity ( lo-fi) simulator hosts minimally embodied agents, which gradually evolve controllers and morphologies to colonize a slow yet high-fidelity ( hi-fi) simulator. The agents are thus physically scaffolded. We show here that, given the same computational budget, these physically scaffolded robots reach higher performance in the hi-fi simulator than do robots that only evolve in the hi-fi simulator, but only for a sufficiently difficult task. These results suggest that a simulation-to-reality pipeline may strike a good balance between accelerating evolution in simulation while anchoring the results in reality, free the investigator from having to prespecify the robot\'s morphology, and pave the way to scalable, automated, robot-generating systems.