Parallel Collision-Free Motion Planning for Robot Trajectories
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Solution Overview
Problem
Existing collision-free motion generation techniques are inefficient in terms of memory, time, and computing resources, leading to suboptimal performance.
Innovation Solution
The implementation of CuRobo functionality, which utilizes parallel processing units (PPUs) to perform collision-free motion generation through algorithms like inverse kinematics (IK) optimization, gradient-based optimization, and model predictive control, enabling simultaneous solution of multiple motion optimization instances in parallel.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional collision-free motion generation methods are used, then motion plans can be generated, but the process consumes excessive memory, time, and computing resources
Solution Approach 1:
The patent segments the motion generation problem into multiple independent optimization instances that can be processed in parallel. Each instance represents a discrete motion planning task that can be solved separately, allowing the system to distribute computational workload across multiple processing units simultaneously, thereby improving productivity while managing computing resource consumption efficiently
Solution Approach 2:
The patent transitions from sequential single-threaded motion generation to parallel multi-threaded processing by adding the time dimension to the computation. Multiple optimization instances are executed concurrently across different processing units, effectively moving from a one-dimensional sequential process to a multi-dimensional parallel process, which dramatically increases motion generation speed
2Loss of time
If traditional collision-free motion generation methods are used, then motion plans can be generated, but the process takes too much time
Solution Approach 1:
The patent divides the complex motion generation task into multiple smaller, independent optimization instances. Each instance can be processed separately and in parallel, reducing the time each individual instance needs to complete while distributing the overall computational load across multiple processing units, thereby reducing total motion generation time without excessively increasing system complexity
Solution Approach 2:
The patent performs preliminary setup by organizing motion instances into batches and preparing optimization parameters before execution. This preliminary organization allows the parallel processing system to efficiently manage and execute multiple instances simultaneously, reducing the actual computation time required for motion generation while maintaining manageable system complexity through structured preprocessing
Data Source
AI summary
Apparatuses, systems, and techniques to perform collision-free motion generation (e.g., to operate a real-world or virtual robot). In at least one embodiment, at least a portion of the collision-free motion generation is performed in parallel.