J. Guo

Dr. J. Guo

Faculty of Aerospace Engineering, Delft University of Technology, 2629 HS Delft, The Netherlands

Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 February 2019 in Swarm Intelligence
Verified
Journal Article
Open access
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MCMario Coppola
Mario Coppola
J. GuoJ. Guo
J. Guo
Eberhard GillEberhard Gill
Eberhard Gill
GCGuido C. H. E. de Croon
Guido C. H. E. de Croon
In this paper we present a procedure to automatically design and verify the local behavior of robots with highly limited cognition. All robots are: anonymous, homogeneous, non-communicating, memoryless, reactive, do not know their global position, do not have global state information, and operate by a local clock. They only know: (1) the relative location of their neighbors within a short range and (2) a common direction (North). We have developed a procedure to generate a local behavior that allows the robots to self-organize into a desired global pattern despite their individual limitations. This is done while also avoiding collisions and keeping the coherence of the swarm at all times. The generated local behavior is a probabilistic local state-action map. The robots follow this stochastic policy to select an action based on their current perception of their neighborhood (i.e., their local state). It is this stochasticity, in fact, that allows the global pattern to eventually emerge. For a generated local behavior, we present a formal proof procedure to verify whether the desired pattern will always eventually emerge from the local actions of the agents. The novelty of the proof procedure is that it is primarily local in nature and focuses on the local states of the robots and the global implications of their local actions. A local approach is of interest to reduce the computational effort as much as possible when verifying the emergence of larger patterns. Finally, we show how the behavior could be implemented on real robots and investigate this with extensive simulations on a realistic robot model. To the best of our knowledge, no other solutions exist for robots with such limited cognition to achieve this level of coordination with proof that the desired global property will emerge.

1 April 2020 in Advances In Space Research
Verified
Journal Article
Closed access
SSSalvatore Sarno
Salvatore Sarno
J. GuoJ. Guo
J. Guo
MDMarco D’Errico
Marco D’Errico
EGE. Gill
E. Gill

1 April 2016 in Acta Astronautica
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Journal Article
Closed access
J. GuoJ. Guo
J. Guo
JBJasper Bouwmeester
Jasper Bouwmeester
Eberhard GillEberhard Gill
Eberhard Gill

1 August 2018 in Aerospace Science and Technology
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Journal Article
Closed access
Zixuan ZhengZixuan Zheng
Zixuan Zheng
J. GuoJ. Guo
J. Guo
Eberhard GillEberhard Gill
Eberhard Gill

1 May 2017 in Progress in Aerospace Sciences
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Journal Article
Closed access
LZLinyu Zhu
Linyu Zhu
J. GuoJ. Guo
J. Guo
Eberhard GillEberhard Gill
Eberhard Gill

29 May 2017 in IEEE Transactions on Aerospace and Electronic Systems
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Journal Article
Closed access
ZMZhongjie Meng
Zhongjie Meng
PHPanfeng Huang
Panfeng Huang
J. GuoJ. Guo
J. Guo
The autonomous maneuverable space net, which consists of a flexible net and several maneuverable units, is a promising solution for the active removal of space debris. A novel dynamics model and a corresponding controller are proposed in this paper to resolve the approach control problem. Given that the net tethers cannot be elongated, interval functions and corresponding constraint forces are exploited to model the unilaterally constrained tethers. The proposed approach dynamics model, which is based on the Hamilton principle, includes distinctive velocity jump phenomena. A dual-loop control scheme with double optimization pseudo-dynamics inversion and sliding mode control is also established. Simulation results validate the feasibility of the proposed control scheme. The net can fly along the expected trajectory without suffering unexpected net deformation or orbital radial movement.