In intelligent warehousing systems, once multiple logistics parcel delivery tasks are assigned to delivery robots, it becomes essential to plan robots’ conflict-free movement paths. These paths must ensure that robots can sequentially complete batch delivery tasks at multiple target locations, including parcel pickup and drop-off locations, as specified in the task assignment plan. Additionally, the operational times for pickup or drop-off at these locations must be considered. To effectively address the challenges of multi-robot, multi-target location path planning in intelligent warehousing systems, this paper proposes a novel path planning method designed for a single robot navigating through multiple target locations. Subsequently, this method enhances traditional algorithms, such as Conflict-Based Search (CBS), Enhanced Conflict-Based Search (ECBS), Meta-Agent Conflict-Based Search (MA-CBS), and Meta-Agent Enhanced Conflict-Based Search (MA-ECBS), to optimize path planning for scenarios involving multiple robots and multiple target locations. These enhanced algorithms lead to the development of four advanced frameworks: CBS-based, ECBS-based, MA-CBS-based, and MA-ECBS-based multi-robot, multi-target path planning methods (MRMTPPM). Case studies have confirmed that CBS-based-MRMTPPM significantly reduces path travel times, while the enhancements to the MA-ECBS-MRMTPPM improve overall planning efficiency.