Work distribution of multiple Cartesian robot arms for kiwifruit harvesting Abstract   Employing multiple robot arms for kiwifruit harvesting can raise the efficiency since the task completion time is shortened. However, task partitioning and reachability are two major concerns. It is found that the task completion time is minimized if task partitions for robot arms are uniform. However, the partition uniformity is influenced by the fruit indivisibility and fruit cluster growing style. It is also constrained by the fruit distribution across the canopy and the robot arm positions which affect the fruit reachability. This article investigates how to partition the tasks of kiwifruit harvesting so that the harvesting can be completed by multiple robot arms in the minimum time with an assumption that the fruits can be harvested by any robot arm. A parameter termed work distribution is introduced to measure how the task partitioning is different from the optimum. A research platform with two robot arms is implemented to show how to approximate the assumption. Ten field experiments of kiwifruit harvesting had been run by the research platform in two kiwifruit orchards in New Zealand with satisfactory outcomes.

Scheduling of Mobile Workstations for Overlapping Production Time and Delivery Time Many existing mobile service robots, including the robots in RobocupHome, perform their designated tasks only when the robots are stationary. The efficiency of these robots can be improved if they can perform some tasks while moving. In this paper, we propose the concept of mobile workstations, which combine mobile platforms with production machinery to increase efficiency by overlapping production time and delivery time. We present a model of mobile workstations and their jobs and describe the task planning algorithm for a team of mobile workstations. The temporal planning problem for mobile workstations combines both features of job shop scheduling problems (JSP) and traveling salesman problem (TSP), but there is little work in the literature that tackles both JSP and TSP simultaneously. Our first algorithm is a complete search algorithm which returns an optimal temporal plan with minimum makespan, and our second algorithm conducts a local search in the space of task graphs so as to quickly return suboptimal temporal plans. According to our experiments, when the number of jobs is small, our second algorithm can generate nearoptimal temporal plans, and when the number of jobs is large, our algorithm can generate much shorter plans than SGPlan 5 and a version of job shop scheduling algorithms.