Evidence map›Paper›PMID 42048674›Full record

ArticleScience progress

Dynamic obstacle avoidance path planning for collaborative robot based on improved APF-Bi-RRT algorithm.

Yufei Li, Li Yan, Maixin Wang, Xiao Wang

Abstract read
In one paragraph

Article in Science progress. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yufei LiSchool of Electrical and Mechanical Engineering, Xi'an Technological University, Xi'an, China.ORCID 0000-0003-0314-2525
Li YanSchool of Electrical and Mechanical Engineering, Xi'an Technological University, Xi'an, China.
Maixin WangSchool of Electrical and Mechanical Engineering, Xi'an Technological University, Xi'an, China.
Xiao WangSchool of Electrical and Mechanical Engineering, Xi'an Technological University, Xi'an, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In order to enable a collaborative robot to perform path planning and operate more smoothly in environments with dynamic obstacles, a dynamic obstacle avoidance algorithm, named improved APF-Bi-RRT, is proposed by combining an improved Artificial Potential Field (APF) and an improved Bidirectional Rapidly-exploring Random Tree (Bi-RRT). First, a cost function is constructed with the goal of minimizing the angle change of each joint of the robot to select path nodes planned by the Bi-RRT algorithm, reducing redundant nodes and improving path quality. Second, considering the influence of dynamic obstacles on the various links of the robot, the gravitational field function of the artificial potential field method is constructed in the joint space, and the repulsive field function is reconstructed. Finally, the two algorithms are combined, and simulations are conducted in environments with static and dynamic obstacles. The results show that the improved APF-Bi-RRT algorithm enables the collaborative robot to achieve dynamic obstacle avoidance with smooth paths and smooth operation of all joints, which verifies the effectiveness of the algorithm.

Indexed as

artificial potential fieldbidirectional rapidly-exploring random treecollaborative robotdynamic obstacle avoidancepath planning

Identifiers

PMID42048674
PMCPMC13145044

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.