As mobile robots become useful performing everyday tasks in complex real-world environments, they must be able to traverse a range of difficult terrain types such as stairs, stepping stones, gaps, jumps and narrow passages. This work investigated traversing these types of environments with a bipedal robot (simulation experiments), and a tracked robot (real world). Developing a traditional monolithic controller for traversing all terrain types is challenging, and for large physical robots realistic test facilities are required and safety must be ensured. An alternative is a suite of simple behaviour controllers that can be composed to achieve complex tasks. This work efficiently trained complex behaviours to enable mobile robots to traverse difficult terrain. By minimising retraining as new behaviours became available, robots were able to traverse increasingly complex terrain sets, leading toward the development of scalable behaviour libraries.

翻译：随着移动机器人在复杂现实环境中执行日常任务变得日益实用，它们必须能够穿越楼梯、踏脚石、间隙、跳跃及狭窄通道等一系列困难地形类型。本研究探索了双足机器人（仿真实验）与履带式机器人（现实环境）穿越此类环境的方法。开发用于穿越所有地形的传统单体控制器极具挑战性，且大型物理机器人需要真实的测试设施并确保安全性。另一种方案是构建一组可组合以实现复杂任务的简单行为控制器。本研究有效训练了复杂行为，使移动机器人能够穿越困难地形。通过在新行为可用时最小化重新训练过程，机器人得以穿越日益复杂的地形组合，进而推动可扩展行为库的开发。