Pith. sign in

REVIEW 1 cited by

A multi-modal table tennis robot system

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2310.19062 v2 pith:2KU7RD7J submitted 2023-10-29 cs.RO cs.AI

classification cs.ROcs.AI
keywords robotsystemtabletennisaccurateapproachcamerasdetection
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

In recent years, robotic table tennis has become a popular research challenge for perception and robot control. Here, we present an improved table tennis robot system with high accuracy vision detection and fast robot reaction. Based on previous work, our system contains a KUKA robot arm with 6 DOF, with four frame-based cameras and two additional event-based cameras. We developed a novel calibration approach to calibrate this multimodal perception system. For table tennis, spin estimation is crucial. Therefore, we introduced a novel, and more accurate spin estimation approach. Finally, we show how combining the output of an event-based camera and a Spiking Neural Network (SNN) can be used for accurate ball detection.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. An Event-Based Perception Pipeline for a Table Tennis Robot

    cs.RO 2025-02 conditional novelty 6.0 of 10

    An event-camera-only perception pipeline detects table tennis balls at about 4,140 updates per second, around 28 times the rate of a frame-based baseline, with comparable pixel accuracy.

Pith tools