Mou Li
Mou Li has a total of 15 co-authors. Here are the top co-authors by number of shared publications:
Liang Tang
2 shared publications- Yao Zhang
Beijing Institute of Technology, Beijing, China
2 shared publications Hao Liu
1 shared publicationHeng Shi
1 shared publicationHuang Huang
1 shared publicationJingrui Zhang
1 shared publication
Latest Publications
- Open Access
- 11 November 2024
- Published by MDPI AG in Applied Sciences
- Vol. 14 (22) , 10377
Multi-Task Agent Hybrid Control in Sparse Maps and Complex Environmental Conditions
With the rapid development of space exploration technology, the detection of extraterrestrial bodies has become increasingly important. Among these, path planning and target recognition and positioning technologies are particularly critical for applications in intelligent agents with low computational power operating in complex environments. This paper presents a novel approach to path planning on low-resolution lunar surface maps by introducing an improved A* algorithm with an adaptive heuristic function. This innovation enhances robustness in environments with limited map accuracy and enables paths that maintain maximum distance from obstacles. Additionally, we innovatively propose the Dynamic Environment Target Identification and Localization (DETIL) algorithm, which identifies unknown obstacles and employs spatiotemporal clustering to locate points of interest. Our main contributions provide valuable references for the aerospace industry, particularly in lunar exploration missions. The simulation results demonstrate that the improved A* algorithm reduces the maximum elevation difference by 55% and the maximum cumulative elevation difference by 68% compared to the traditional A* algorithm. Furthermore, the DETIL algorithm’s obstacle identification component successfully recognizes all the obstacles along the path, and its spatiotemporal clustering improves the average number of target discoveries by 152% over the conventional DBSCAN clustering approach.
- 11 November 2024
- Published by MDPI AG in Applied Sciences
- Vol. 14 (22) , 10377
Open AccessMulti-Task Agent Hybrid Control in Sparse Maps and Complex Environmental Conditions
With the rapid development of space exploration technology, the detection of extraterrestrial bodies has become increasingly important. Among these, path planning and target recognition and positioning technologies are particularly critical for applications in intelligent agents with low computational power operating in complex environments. This paper presents a novel approach to path planning on low-resolution lunar surface maps by introducing an improved A* algorithm with an adaptive heuristic function. This innovation enhances robustness in environments with limited map accuracy and enables paths that maintain maximum distance from obstacles. Additionally, we innovatively propose the Dynamic Environment Target Identification and Localization (DETIL) algorithm, which identifies unknown obstacles and employs spatiotemporal clustering to locate points of interest. Our main contributions provide valuable references for the aerospace industry, particularly in lunar exploration missions. The simulation results demonstrate that the improved A* algorithm reduces the maximum elevation difference by 55% and the maximum cumulative elevation difference by 68% compared to the traditional A* algorithm. Furthermore, the DETIL algorithm’s obstacle identification component successfully recognizes all the obstacles along the path, and its spatiotemporal clustering improves the average number of target discoveries by 152% over the conventional DBSCAN clustering approach.
- 1 June 2024
- Published by Institute of Electrical and Electronics Engineers (IEEE) in Journal of Systems Engineering and Electronics
- Vol. 35 (3) , 753-768
Contact Detumbling Toward a Nutating Target Through Deformable Effectors and Prescribed Performance Controller
Detumbling operation toward a rotating target with nutation is meaningful for debris removal but challenging. In this study, a deformable end-effector is first designed based on the requirements for contacting the nutating target. A dual-arm robotic system installed with the deformable end-effectors is modeled and the movement of the end-tips is analyzed. The complex operation of the contact toward a nutating target places strict requirements on control accuracy and controller robustness. Thus, an improvement of the tracking error transformation is proposed and an adaptive sliding mode controller with prescribed performance is designed to guarantee the fast and precise motion of the effector during the contact detumbling. Finally, by employing the proposed effector and the controller, numerical simulations are carried out to verify the effectiveness and efficiency of the contact detumbling toward a nutating target.
- 1 June 2024
- Published by Institute of Electrical and Electronics Engineers (IEEE) in Journal of Systems Engineering and Electronics
- Vol. 35 (3) , 753-768
Contact Detumbling Toward a Nutating Target Through Deformable Effectors and Prescribed Performance Controller
Detumbling operation toward a rotating target with nutation is meaningful for debris removal but challenging. In this study, a deformable end-effector is first designed based on the requirements for contacting the nutating target. A dual-arm robotic system installed with the deformable end-effectors is modeled and the movement of the end-tips is analyzed. The complex operation of the contact toward a nutating target places strict requirements on control accuracy and controller robustness. Thus, an improvement of the tracking error transformation is proposed and an adaptive sliding mode controller with prescribed performance is designed to guarantee the fast and precise motion of the effector during the contact detumbling. Finally, by employing the proposed effector and the controller, numerical simulations are carried out to verify the effectiveness and efficiency of the contact detumbling toward a nutating target.
- 3 June 2022
- Published by Elsevier in Acta Astronautica
- Vol. 198, 9-25
Near-optimal interception strategy for orbital pursuit-evasion using deep reinforcement learning
- 3 June 2022
- Published by Elsevier in Acta Astronautica
- Vol. 198, 9-25
Near-optimal interception strategy for orbital pursuit-evasion using deep reinforcement learning
- 19 January 2022
- Published by Elsevier in Acta Astronautica
- Vol. 193, 303-310
Autonomous collision avoidance sample grasping method for extraterrestrial exploration
- 19 January 2022
- Published by Elsevier in Acta Astronautica
- Vol. 193, 303-310
Autonomous collision avoidance sample grasping method for extraterrestrial exploration