摘要
一位新闻记者兼机器人与机器学习的新闻编辑每日新闻-机器人的研究发现被用在一份新的报告中。根据NewsRx记者在Minneapolis,M Inesota的新闻报道，研究表明，“我们解决了移动机器人的运动规划和控制问题，以满足信号时序逻辑(STL)规范所描述的丰富的、时变的任务。该规范可能包含嵌套时序运算符或时间冲突要求的任务（例如，实现周期性任务或在同一时间间隔内定义的任务）。”新闻记者从明尼索塔大学的研究中获得了一句话：“此外，任务可以定义在随时间变化的地点（即动态目标），”该方法考虑了机器人的驱动极限和STL任务的可行序列,定义了系统必须始终保持在内部的时变可行状态集,并给出了可行序列.生成过程包括周期性任务的分解和因分离算子而产生的可选场景，并用该序列定义CBFs，保证了STL的满足，并给出了一些理论结果。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on Robotics are disc ussed in a new report. According to news reporting originating in Minneapolis, M innesota, by NewsRx journalists, research stated, “We address a motion planning and control problem for mobile robots to satisfy rich, time -varying tasks expre ssed as Signal Temporal Logic (STL) specifications. The specifications may inclu de tasks with nested temporal operators or time -conflicting requirements (e.g., achieving periodic tasks or tasks defined within the same time interval).” The news reporters obtained a quote from the research from the University of Min nesota, “Moreover, the tasks can be defined in locations changing with time (i.e ., dynamic targets), and their future motions are not known a priori. This unpre dictability requires an online control approach which motivates us to investigat e the use of control barrier functions (CBFs). The proposed CBFs take into accou nt the actuation limits of the robots and a feasible sequence of STL tasks. They define time -varying feasible sets of states the system must always stay inside . We show the feasible sequence generation process that even includes the decomp osition of periodic tasks and alternative scenarios due to disjunction operators . The sequence is used to define CBFs, ensuring STL satisfaction. We also show s ome theoretical results on the correctness of the proposed method.”
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