For a robotic bin-managing system working in an orchard environment, especially in modern narrow row spaced orchards in the Pacific Northwest (PNW) region of the U.S., path planning is an essential function to achieve highly efficient bin management. Unlike path planning for a car-like vehicle in an open field, path planning for a four-wheel-independent-steered (4WIS) robotic bin-managing platform in orchard environment is much more challenging due to the very confined working space between tree rows. Subject to the unique constraints of worksite space and operation limits, different steering modes are often required to accomplish the desired bin handling maneuvering actions effectively, or sometimes even all. In this study, we proposed a path planning algorithm to guide the robotic system in accomplishing several designated bin management tasks effectively, such as correcting pose error between tree rows; entering a tree lane from the headland; and loading a bin between tree rows. The path planning algorithm selects among the three steering modes of 1) Ackermann steering, 2) Active-front-and-rear steering, and 3) combination of spinning steering and crab steering to accomplish those tasks effectively.  This algorithm includes a four-step optimization strategy for determining the optimal steering mode for different situations. Firstly, it computes the initial and ending postures of the robotic system, and then calculates possible paths connecting both postures for the three steering modes in absence of obstacles and worksite boundaries. In the third step, unsuitable paths are filtered out according to the obstacles and boundaries of worksites. Eventually an optimized path in terms of shortest path length is picked from the rest of admissible paths. The developed path planning algorithm was simulated in the Matlab environment to validate its accuracy, and then implemented with a self-propelled robotic platform “bin-dog” system equipped with a 4WIS system in commercial orchard environment to validate its functionalities.