Guiding Autonomous Exploration With Signal Temporal Logic

被引:22
作者
Barbosa, Fernando S. [1 ]
Duberg, Daniel [1 ]
Jensfelt, Patric [1 ]
Tumova, Jana [1 ]
机构
[1] KTH Royal Inst Technol, Div Robot Percept & Learning, S-11428 Stockholm, Sweden
关键词
Mapping; motion and path planning; formal methods in robotics and automation; search and rescue robots;
D O I
10.1109/LRA.2019.2926669
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
Algorithms for autonomous robotic exploration usually focus on optimizing time and coverage, often in a greedy fashion. However, obstacle inflation is conservative and might limit mapping capabilities and even prevent the robot from moving through narrow, important places. This letter proposes a method to influence the manner the robot moves in the environment by taking into consideration a user-defined spatial preference formulated in a fragment of signal temporal logic (STL). We propose to guide the motion planning toward minimizing the violation of such preference through a cost function that integrates the quantitative semantics, i.e., robustness of STL. To demonstrate the effectiveness of the proposed approach, we integrate it into the autonomous exploration planner (AEP). Results from simulations and real-world experiments are presented, highlighting the benefits of our approach.
引用
收藏
页码:3332 / 3339
页数:8
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