# A neural signed configuration distance function for path planning of picking manipulators

Source: [A neural signed configuration distance function for path planning of picking manipulators](<https://www.sota2.com/research/paper/68fa77231e209131cea71554>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-05-27T05:00:21.000Z

Authors: Bernhard Wullt, Mikael Norrl\\"of, Per Mattsson, Thomas B. Sch\\"on

Published: 2025-02-22T12:18:13.000Z

## Abstract

Picking manipulators are task specific robots, with fewer degrees of freedom compared to general-purpose manipulators, and are heavily used in industry. The efficiency of the picking robots is highly dependent on the path planning solution, which is commonly based on sampling-based multi-query methods. The planner is robustly able to solve the problem, but its heavy use of collision-detection limits the planning capabilities for online use. We approach this problem by presenting a novel implicit obstacle representation for path planning, a neural signed configuration distance function (nSCDF), which allows us to form collision-free balls in the configuration space. We use the ball representation to re-formulate a state of the art multi-query path planner, i.e., instead of points, we use balls in the graph. Our planner returns a collision-free corridor, which allows us to use convex programming to produce optimized paths. From our numerical experiments, we observe that our planner produces paths that are close to those from an asymptotically optimal path planner, in significantly less time.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Path Planning on MR](<https://www.sota2.com/research/sota/path-planning-on-mr.md>): Path planning; MR; Time (ms): 0.62.

- [Path Planning on SC3](<https://www.sota2.com/research/sota/path-planning-on-sc3.md>): Path planning; SC3; Time (ms): 1.85.

- [Path Planning on SC4](<https://www.sota2.com/research/sota/path-planning-on-sc4.md>): Path planning; SC4; Time (ms): 3.92.

- [Path Planning on WD](<https://www.sota2.com/research/sota/path-planning-on-wd.md>): Path planning; WD; Time (ms): 0.95.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2502.16205>)

[PDF](<https://arxiv.org/pdf/2502.16205.pdf>)