arXiv subjects

Liding Zhang

Publications and source records attributed to Liding Zhang.

22 records · Page 2Linked to original sources

arXiv2024

Flexible Informed Trees (FIT*): Adaptive Batch-Size Approach in Informed Sampling-Based Path Planning

In path planning, anytime almost-surely asymptotically optimal planners dominate the benchmark of sampling-based planners. A notable example is Batch Informed Trees (BIT*), where planners iteratively determine paths to batches of vertices within the exploration area. However, utilizing a consistent batch size is inefficient for initial pathfinding and optimal performance, it relies on effective task allocation. This paper introduces Flexible Informed Trees (FIT*), a sampling-based planner that integrates an adaptive batch-size method to enhance the initial path convergence rate. FIT* employs a flexible approach in adjusting batch sizes dynamically based on the inherent dimension of the configuration spaces and the hypervolume of the n-dimensional hyperellipsoid. By applying dense and sparse sampling strategy, FIT* improves convergence rate while finding successful solutions faster with lower initial solution cost. This method enhances the planner's ability to handle confined, narrow spaces in the initial finding phase and increases batch vertices sampling frequency in the optimization phase. FIT* outperforms existing single-query, sampling-based planners on the tested problems in R^2 to R^8, and was demonstrated on a real-world mobile manipulation task.

cs.RO↗

arXiv2024

Online Efficient Safety-Critical Control for Mobile Robots in Unknown Dynamic Multi-Obstacle Environments

This paper proposes a LiDAR-based goal-seeking and exploration framework, addressing the efficiency of online obstacle avoidance in unstructured environments populated with static and moving obstacles. This framework addresses two significant challenges associated with traditional dynamic control barrier functions (D-CBFs): their online construction and the diminished real-time performance caused by utilizing multiple D-CBFs. To tackle the first challenge, the framework's perception component begins with clustering point clouds via the DBSCAN algorithm, followed by encapsulating these clusters with the minimum bounding ellipses (MBEs) algorithm to create elliptical representations. By comparing the current state of MBEs with those stored from previous moments, the differentiation between static and dynamic obstacles is realized, and the Kalman filter is utilized to predict the movements of the latter. Such analysis facilitates the D-CBF's online construction for each MBE. To tackle the second challenge, we introduce buffer zones, generating Type-II D-CBFs online for each identified obstacle. Utilizing these buffer zones as activation areas substantially reduces the number of D-CBFs that need to be activated. Upon entering these buffer zones, the system prioritizes safety, autonomously navigating safe paths, and hence referred to as the exploration mode. Exiting these buffer zones triggers the system's transition to goal-seeking mode. We demonstrate that the system's states under this framework achieve safety and asymptotic stabilization. Experimental results in simulated and real-world environments have validated our framework's capability, allowing a LiDAR-equipped mobile robot to efficiently and safely reach the desired location within dynamic environments containing multiple obstacles.

cs.RO↗

arXiv2024

Real-time Contact State Estimation in Shape Control of Deformable Linear Objects under Small Environmental Constraints

Controlling the shape of deformable linear objects using robots and constraints provided by environmental fixtures has diverse industrial applications. In order to establish robust contacts with these fixtures, accurate estimation of the contact state is essential for preventing and rectifying potential anomalies. However, this task is challenging due to the small sizes of fixtures, the requirement for real-time performances, and the infinite degrees of freedom of the deformable linear objects. In this paper, we propose a real-time approach for estimating both contact establishment and subsequent changes by leveraging the dependency between the applied and detected contact force on the deformable linear objects. We seamlessly integrate this method into the robot control loop and achieve an adaptive shape control framework which avoids, detects and corrects anomalies automatically. Real-world experiments validate the robustness and effectiveness of our contact estimation approach across various scenarios, significantly increasing the success rate of shape control processes.

cs.RO↗

arXiv2019

Cyano-functionalized Ag-bis-acetylide wires on Ag(110)

Organometallic nanostructures are promising candidates for applications in optoelectronics, magnetism and catalysis. Our bottom-up approach employs a cyano-functionalized terminal alkyne species (CN-DETP) on the Ag(110) surface to fabricate 2D domains of regularly stacked Ag-acetylide nanowires. We unravel their adsorption properties and give evidence to their organometallic character with the aid of complementary surface-sensitive techniques, i.e. scanning tunneling microscopy, X-ray photoelectron spectroscopy and near-edge X-ray absorption fine-structure spectroscopy. Guided by the anisotropic (110) surface, highly oriented nanowires form in two enantiomorphic domains of regularly stacked trans isomers, whereby the bifunctional design of CN-DETP gives rise to orthogonal bonding motifs. Based on STM imaging, we find high thermal stability of the Ag-bis-acetylide wires, without conversion into graphdiyne chains. Our approach based on orthogonal bifunctionalization and selective functional group recognition extends the toolbox of creating alkyne-based nanostructures at interfaces.

physics.app-ph↗