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Jianping He

17 papers hereh-index 5117 citations39 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author9
  • last author7

Across the 16 of 17 papers where every author was matched, so the position is known.

fields
  • cs.RO8
  • eess.SY5
  • cs.LG3
  • math.OC1
same name
  • Jianping He — 16 papers, h 35
  • Jianping He — 13 papers, h 8
  • Jianping He — 9 papers, h 3
  • Jianping He — 5 papers, h 1
  • Jianping He — 3 papers, h 7
  • Jianping He — 2 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20222026
most citedAffordance-Driven Next-Best-View Planning for Robotic Grasping

6 citations · 7 across the 17 of their papers we have counts for

collaborators
Showing 2025Show all

4 papers · 1 filter

eess.SY2025

Optimal Unpredictable Control for Linear Systems

Chendi Qu, Jianping He, Jialun Li +1

In this paper, we investigate how to achieve the unpredictability against malicious inferences for linear systems. The key idea is to add stochastic control inputs, named as unpred…

eess.SY2025

Pursuit-Evasion Between a Velocity-Constrained Double-Integrator Pursuer and a Single-Integrator Evader

Zehua Zhao, Rui Yan, Jianping He +2

We study a pursuit-evasion game between a double integrator-driven pursuer with bounded velocity and bounded acceleration and a single integrator-driven evader with bounded velocit…

eess.SY2025

Formation Maneuver Control Based on the Augmented Laplacian Method

Xinzhe Zhou, Xuyang Wang, Xiaoming Duan +2

This paper proposes a novel formation maneuver control method for both 2-D and 3-D space, which enables the formation to translate, scale, and rotate with arbitrary orientation. Th…

cs.LG2025

Analysis of On-policy Policy Gradient Methods under the Distribution Mismatch

Weizhen Wang, Jianping He, Xinzhe Zhou +1

Policy gradient methods are among the most successful approaches for solving challenging reinforcement learning problems. Despite their empirical success, many state-of-the-art pol…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.