Object Recognition Using Tactile Measurements: Kernel Sparse Coding Methods

@article{Liu2016ObjectRU,
  title={Object Recognition Using Tactile Measurements: Kernel Sparse Coding Methods},
  author={Huaping Liu and Di Guo and Fuchun Sun},
  journal={IEEE Transactions on Instrumentation and Measurement},
  year={2016},
  volume={65},
  pages={656-665}
}
Dexterous robots have emerged in the last decade in response to the need for fine-motor-control assistance in applications as diverse as surgery, undersea welding, and mechanical manipulation in space. Crucial to the fine operation and contact environmental perception are tactile sensors that are fixed on the robotic fingertips. These can be used to distinguish material texture, roughness, spatial features, compliance, and friction. In this paper, we regard the investigated tactile data as time… CONTINUE READING
Highly Cited
This paper has 116 citations. REVIEW CITATIONS
44 Citations
38 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 44 extracted citations

116 Citations

050100201620172018
Citations per Year
Semantic Scholar estimates that this publication has 116 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 38 references

Data fusion-based resilient control system under DoS attacks: A game theoretic approach

  • Y. Yuan, F. Sun
  • Int. J. Control Autom. Syst., vol. 13, no. 3, pp…
  • 2015
1 Excerpt

Similar Papers

Loading similar papers…