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An online trajectory guidance framework via imitation learning and interactive feedback in robot-assisted surgery

NEURAL NETWORKS 2025年 185卷 107197页

作者： Chen, Ziyang Fan, Ke Politecn Milan Dept Elect Informat & Bioengn I-20133 Milan Italy

Improving the manipulation performance of surgical instruments is important for novice surgeons, as it directly affects the safety and outcome of robot-assisted surgery. To reduce the difference between expert and novice surgeons, learning the instrument movement trajectories generated by experts is an effective approach for novices to foster their muscle memory and improve manipulation skills. In this work, we propose an online trajectory guidance framework to generate expert-like movement trajectories so that novice surgeons can receive intra-operative trajectory guidance to achieve a similar manipulation performance as experts. First, Dynamic Movement Primitives (DMP) based Imitation Learning (IL) is implemented to model the 3D trajectories demonstrated by experts for adaptive trajectory generation at different start and end points. To introduce the obstacle avoidance capability into IL, we propose a vision-based strategy involving stereo reconstruction, object detection and segmentation to recover the 3D information of obstacles so that they can be coupled into DMP as an obstacle avoidance term. Furthermore, we introduce Augmented Reality (AR) and Interactive Feedback (IF) including visual and force feedback to enhance the trajectory reproduction accuracy of novice surgeons during operation. The experiment was conducted based on a 3D peg-transfer task in two different scenes (with changed start and end points, and with the obstacle present) using a standard da Vinci Research Kit robot. Ten non-expert human subjects were invited to evaluate the online trajectory guidance framework by reproducing the expert-like manipulation trajectories, and the experimental results showed that the novices with the assistance of AR and IF achieved promising trajectory reproduction performance (the mean distance error Emean was reduced by 76.47% and 65.15% in two different intra-operative scenes, respectively), narrowing the manipulation gap with experts.

关键词： Robotic surgery trajectory guidance Imitation learning Augmented reality Interactive feedback

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An Integrated trajectory guidance and Attitude Control Law with Enhanced Anti Disturbance Capability for Mars Pinpoint Landing 4

An Integrated Trajectory Guidance and Attitude Control Law w...

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4th International Conference on Information Science and Control Engineering (ICISCE)

作者： Zhang, Yabin Yang, Tingting Beihang Univ Key Lab Micronano Measurement Manipulat & Phys Sch Phys & Nucl Energy Engn Beijing Peoples R China China Patent Informat Ctr State Intellectual Property Off PRC Beijing Peoples R China

ISBN: (纸本)9781538630136

guidance and control accuracy could be essentially improved by using the unified algorithm for a Mars lander compared with the traditional algorithm and a novel integrated trajectory guidance and attitude control law is presented in this paper. In a Mars mission there will be various disturbances and the actual trajectory and attitude of a Mars lander will be directly affected seriously. In the proposed algorithm the effect of major disturbance could be estimated through a disturbance observer and then it will be incorporated in the feed-forward compensation. And the residual other disturbances could be attenuated by the multiple sliding surfaces techniques. Such a composite hierarchical framework is composed of the feedforward compensation and the feedback control. This strategy does not require a pre-computed reference trajectory and it could be applied to reduce the conservatism of the system. Its global stability is verified using Lyapunov-based approach. Simulation results show that this algorithm could guide and control the Mars lander safely and accurately according to the Mars mission, which has enhanced anti-disturbance capability comparing with traditional law in the presence of disturbances.

关键词： Mars pinpoint landing powered descent trajectory guidance attitude control disturbance observer based control

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MLS: A Meta-Learning Based Stackelberg Model for Robot trajectory guidance 8

MLS: A Meta-Learning Based Stackelberg Model for Robot Traje...

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8th International Conference on Robotics, Control and Automation (ICRCA)

作者： Guo, Jin Jiang, Zhiyong Liu, Yifan Gong, Lili China Elect Technol Grp Corp Res Inst 21 Robot Engn Ctr Shanghai Peoples R China Shanghai Publishing & Printing Coll Off Acad Res Shanghai Peoples R China

ISBN: (纸本)9798350344738;9798350344721

The critical role of trajectory guidance in facilitating follower robots to reach target destinations under the supervision of a leader robot is well-established. However, the complexity of coordinating efficient collaboration increases when a leader must guide a diverse set of followers with unknown specific characteristics. To address this challenge, we propose a novel meta-learning-based Stackelberg approach. We model the guided trajectory planning problem as a dynamic Stackelberg game, capturing the intricate interaction dynamics between the leader and followers. Utilizing meta-learning techniques, the leader learns a meta-best-response model from a selected set of followers. When a follower initiates a guidance request, the leader swiftly adapts to the follower's unique characteristics using a few learning data. This follower-specific model is then used for effective trajectory guidance. Comprehensive simulations demonstrate the superior generalization and adaptability of our proposed method over alternative learning methods, and emphasize the practical value and effectiveness of the guidance mechanism. Our findings underscore the potential of our meta-learning-based Stackelberg approach in addressing collaborative trajectory planning challenges in heterogeneous multi-robot systems.

关键词： trajectory guidance robot agent meta learning Stackelberg game

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PARALLEL COMPUTATION OF 2-POINT BOUNDARY-VALUE-PROBLEMS VIA PARTICULAR SOLUTIONS

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JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 1993年第1期79卷 5-29页

作者： MIELE, A WANG, T 1. Aero-Astronautics Group Rice University Houston Texas

Nonlinear two-point boundary-value problems (TPBVP) can be reduced to the iterative solution of a sequence of linear problems by means of quasilinearization techniques. Therefore, the efficient solution of linear problems is the key to the efficient solution of nonlinear problems. Among the techniques available for solving linear two-point boundary-value problems, the method of particular solutions (MPS) is particularly attractive in that it employs only one differential system, the original nonhomogeneous system, albeit with different initial conditions. This feature of MPS makes it ideally suitable for implementation on parallel computers in that the following requirements are met: the computational effort is subdivided into separate tasks (particular solutions) assigned to the different processors;the tasks have nearly the same size;there is little intercommunication between the tasks. For the TPBVP, the speedup achievable is of O(n), where n is the dimension of the state vector, hence relatively modest for the differential systems of interest in trajectory optimization and guidance. This being the case, we transform the TPBVP into a multi-point boundary-value problem (MPBVP) involving m time subintervals, with m-l continuity conditions imposed at the interface of contiguous subintervals. For the MPBVP, the speedup achievable is of O(mn), hence substantially higher than that achievable for the TPBVP. It reduces to O(m) if the parallelism is implemented only in the time domain and not in the state domain. A drawback of the multi-point approach is that it requires the solution of a large linear algebraic system for the constants of the particular solutions. This drawback can be offset by exploiting the particular nature of the interface conditions: if the vector of constants for the first subinterval is known, the vector of constants for the subsequent subintervals can be obtained with linear transformations. Using decomposition techniques together with the discret

关键词： 2-POINT BOUNDARY-VALUE PROBLEMS MULTIPOINT BOUNDARY-VALUE PROBLEMS MODIFIED QUASI-LINEARIZATION ALGORITHM METHOD OF PARTICULAR SOLUTIONS SEQUENTIAL ALGORITHMS PARALLEL ALGORITHMS, PARALLEL COMPUTATION trajectory OPTIMIZATION trajectory guidance

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Multi-model direct generalised predictive control for automatic train operation system

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IET INTELLIGENT TRANSPORT SYSTEMS 2015年第1期9卷 86-94页

作者： Wen, Shuhuan Yang, Jingwei Rad, Ahmad B. Hao, Pengcheng Yanshan Univ Key Lab Ind Comp Control Engn Hebei Prov Qinhuangdao 066004 Peoples R China Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing Peoples R China Simon Fraser Univ Sch Engn Sci Surrey BC V3T 0A3 Canada

The authors propose a novel multi-model direct generalised predictive control based on predictive function control (PFC) algorithm for automatic train operation system. The proposed method facilitates autonomous driving of a train through a given guidance trajectory. Firstly, they present a multi-model architecture based on fuzzy c-means clustering algorithm. In order to obtain the optimal number of sub-linear models, they apply Xie-Beni cluster validity index. In this regards, the multi-model set is established off-line. Secondly, the proper sub-linear model is selected as the predictive model by using switching performance index at each time slot. The control variables are calculated by direct generalised predictive controller based on PFC. The control algorithm is simple, and can reduce the on-line computation time by directly identifies the unknown parameters in the controller. It can avoid recursively solving the Diophantine equations. The calculation of compensation value becomes simple by introducing PFC. Finally, simulation results are provided to show the effectiveness of the proposed scheme.

关键词： predictive control trajectory control fuzzy set theory pattern clustering performance index time-varying systems railways rail traffic control multimodel direct generalised predictive control automatic train operation system predictive function control algorithm PFC algorithm autonomous train driving trajectory guidance multimodel architecture fuzzy c-means clustering algorithm sublinear models Xie-Beni cluster validity index sublinear model switching performance index online computation time Diophantine equations compensation value

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Vision-based UAV Landing on the Moving Vehicle

Vision-based UAV Landing on the Moving Vehicle

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Lee, Hanscob Jung, Scokwoo Shim, David Hyunchul Korea Adv Inst Sci & Technol Dept Aerosp Engn Daejeon South Korea

ISBN: (纸本)9781467393331

This paper describes the tracking guidance for the autonomous UAV landing and the vision-based detection of the marker on the moving vehicle with the real-time image processing system. The detection of the marker is based on the color detection algorithm with morphological filter and the tracking guidance is based on the relative distance between the UAV and the vehicle. In order to track and land on the moving vehicle, we have built the integrated system on the UAV platform that conducts the landing mission with the on-board image processing system. The flight test was performed with the moving vehicle in the outdoor environment, and we validated the algorithm for the vision-based autonomous landing.

关键词： Unmanned Aerial Vehicle (UAV) Vision-based Detection Morphological Filter Target Tracking trajectory guidance On-board Image Processing

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Multi-model direct generalised predictive control for automatic train operation system

Multi-model direct generalised predictive control for automa...

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20th ITS World Congress

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Ascent guidance for an Aerospace Plane

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IFAC Proceedings Volumes 1992年第22期25卷 489-494页

作者： K.D. Mease Department of Mechanical and Aerospace Engineering Princeton University Princeton NJ 08544-5263 USA

A single-stage vehicle using airbreathing propulsion holds promise for a more economical delivery of payloads to orbit. The utility of the vehicle is contingent on having a guidance capability for flying a near minimum-fuel ascent trajectory. The challenges in ascent guidance are identified via an analysis of the guidance problem relative to that for the U.S. Space Shuttle. Feedback guidance logic for the hypersonic phase of a near-minimum-fuel ascent trajectory is described. The two-time-scale nature of the vehicle translational dynamics allows the translational state space to be decomposed approximately into an invariant slow manifold and an invariant foliation of fast manifolds. Robust near-optimal guidance is synthesized as a composite of the minimum-fuel control on the slow manifold—as determined by the dynamic pressure and heat rate constraints—and a fast, control for robust tracking of the slow manifold in the presence of atmospheric disturbances and modeling errors. The tracking control is designed using feedback linearization and the bandwidth-limited variable structure control method. Simulations indicate the effectiveness of the guidance logic.

关键词： Aerospace Plane trajectory guidance Singular Perturbations Feedback Linearization Variable Structure Control

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