Robotic Pallet Placement Using Bounded Tree Search Look-Ahead
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Solution Overview
Problem
The challenge of efficiently stacking dissimilar items on a pallet without causing instability or damage, particularly in environments with varied item sizes, weights, and types, is exacerbated by the need to consider future items in the sequence, leading to computationally burdensome scenario simulations.
Innovation Solution
A robotic system employs a tree-search approach with pruning techniques to determine optimal item placements, using bounded tree searches and heuristics to explore a reduced search space, ensuring stability and efficiency by simulating a subset of possible scenarios and applying spacers as needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system simulates all possible future scenarios to determine optimal item placement, then the stability and optimality of palletization is improved, but the computational complexity and time required increases significantly
Solution Approach 1:
The patent segments the search space by organizing possible item placements into a tree structure with levels corresponding to different items in the sequence. This segmentation allows the system to explore placements systematically without evaluating all possible scenarios simultaneously, reducing computational complexity while maintaining optimization quality.
Solution Approach 2:
The patent applies preliminary action by performing bounded tree searches that look ahead a limited number of items in the sequence. This allows the system to anticipate future placements and make optimal current decisions without simulating all possible future scenarios, thereby improving palletization stability while controlling computational resources.
2Volume of moving object
If the system performs comprehensive scenario simulations to ensure optimal item placement, then the space efficiency of palletization is improved, but the processing time and latency increase
Solution Approach 1:
The patent implements partial action by performing bounded tree searches that evaluate only a subset of possible future scenarios rather than all possible placements. This partial exploration achieves sufficient space efficiency optimization while significantly reducing processing time and latency compared to comprehensive simulations.
Solution Approach 2:
By performing limited look-ahead searches in advance, the system prepares optimal placement decisions without waiting for complete scenario simulations. This preliminary action enables real-time or near-real-time palletization while achieving good space utilization.
3Manufacturing precision
If the system uses unbounded tree search to explore all placement options, then the optimality of item arrangement is improved, but the computational resources and energy consumption increase
Solution Approach 1:
The patent segments the exhaustive search into bounded tree searches with limited depth corresponding to a specific number of future items. This segmentation maintains placement optimality by considering future constraints while reducing computational energy consumption by avoiding evaluation of all possible scenarios.
Solution Approach 2:
The patent dynamically adjusts the search depth and scope of tree searches based on computational resource availability and item characteristics. This dynamic approach maintains optimality where needed while reducing energy consumption in less critical scenarios, achieving a balance between placement quality and resource usage.
Data Source
AI summary
A robotic system is disclosed. The system includes a communication interface that receives, from one or more sensors deployed in a workspace, sensor data indicative of a current state of the workspace. The system includes one or more processors that use the sensor data to estimate a state of one or both of the pallet or other receptacle and the set of zero or more items stacked on or in the receptacle, and use the estimated state to generate or update a plan to control a robotic arm to place a next set of items on or in, or remove the next set of items from, the pallet or other receptacle, the plan comprising an ordered sequence of item placements or removals. The plan is generated or updated based at least in part by performing a bounded tree search in which a subset of possible ordered sequences is explored.