Abstract
A typical commercial berry farm is spread across quite a few hectares and has over hundreds of rows and tens of pickers operating on a daily basis. The berries in these farms are grown in a poly-tunnel parallel row based environment. This work develops a heuristic assignment technique called Smart Parking. Smart Parking is used for allocating parking spaces to autonomous transportation robots that assist fruit pickers working in such farms. The Smart Parking algorithm developed is put to test in a simulation software. It is also integrated with a robot controller called RASberry, which is a cutting-edge research project for running an entirely automated strawberry farm. The robots utilised for autonomous transportation in the RASberry project and the real-world trials in this study are Thorvald by Saga Robotics. To monitor and evaluate the effectiveness of Smart Parking, a number of real-world tests are carried out using the RASberry-Thorvald system. Smart Parking performs better than Standard Parking in terms of mechanical conservation and task completion time, as shown by graphical trend lines and statistical tests.
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The Engineering and Physical Sciences Research Council [EP/S023917/1] and Saga Robotics provided funding for this work.
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Ravikanna, R. et al. (2023). Smart Parking System Using Heuristic Optimization for Autonomous Transportation Robots in Agriculture. In: Iida, F., Maiolino, P., Abdulali, A., Wang, M. (eds) Towards Autonomous Robotic Systems. TAROS 2023. Lecture Notes in Computer Science(), vol 14136. Springer, Cham. https://doi.org/10.1007/978-3-031-43360-3_4
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