In this paper, we study the Orienteering Aisle-graphs Single-access Problem (OASP), a variant of the orienteering problem for a robot moving in a so-called single-access aisle-graph, i.e., a graph consisting of a set of rows that can be accessed from one side only. Aisle-graphs model, among others, vineyards or warehouses. Each aisle-graph vertex is associated with a reward that a robot obtains when visits the vertex itself. As the robot's energy is limited, only a subset of vertices can be visited with a fully charged battery. The objective is to maximize the total reward collected by the robot with a battery charge. We first propose an optimal algorithm that solves OASP in O(m^2 n^2) time for aisle-graphs with a single access consisting of m rows, each with n vertices. With the goal of designing faster solutions, we propose four greedy sub-optimal algorithms that run in at most O(mn (m+n)) time. For two of them, we guarantee an approximation ratio of 1/2(1-1/e), where e is the base of the natural logarithm, on the total reward by exploiting the well-known submodularity property. Experimentally, we show that these algorithms collect more than 80% of the optimal reward.

翻译：在本文中,我们研究了“Orienteering Aisle-graphs Aisle-graphs 单进入问题(OASP),这是机器人在所谓的单进入过道图中移动的“定向”问题的变种,即由一组只能从一边访问的行组成的图表。Aisle-graphs模型,包括葡萄园或仓库等。每个过道顶部都与机器人在访问顶端本身时获得的奖赏有关。由于机器人的能量有限,只能用一个完全充电的电池查看一个顶端子。目标是最大限度地增加机器人在电池充电时收集的全部奖赏。我们首先提出一种最佳算法,在O(m)2 nü2) 中用单访问行(包括葡萄园或仓库)的时间解决O(m) ASCP的一组行。每个过道顶端都与机器人在访问顶端时获得的奖赏有关。我们提议了四种最佳的亚最佳算法,在大多数O/m(m+n)时间运行。对于两个机器人来说,我们用电池充电电池充电的电池充电的奖率中,我们保证在80次轨道上采集的80号上采集。