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FineCog-Nav: Integrating Fine-grained Cognitive Modules for Zero-shot Multimodal UAV Navigation DENALI: A Dataset Enabling Non-Line-of-Sight Spatial Reasoning with Low-Cost LiDARs SENSE: Stereo OpEN Vocabulary SEmantic Segmentation Continual Hand-Eye Calibration for Open-world Robotic Manipulation PLAF: Pixel-wise Language-Aligned Feature Extraction for Efficient 3D Scene Understanding GaussianFlow SLAM: Monocular Gaussian Splatting SLAM Guided by GaussianFlow GIST: Multimodal Knowledge Extraction and Spatial Grounding via Intelligent Semantic Topology $π_{0.7}$: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities R3D: Revisiting 3D Policy Learning Vision-Based Safe Human-Robot Collaboration with Uncertainty Guarantees Benchmarking Classical Coverage Path Planning Heuristics on Irregular Hexagonal Grids for Maritime Coverage Scenarios NEAT-NC: NEAT guided Navigation Cells for Robot Path Planning HRDexDB: A Large-Scale Dataset of Dexterous Human and Robotic Hand Grasps ADAPT: Benchmarking Commonsense Planning under Unspecified Affordance Constraints An Intelligent Robotic and Bio-Digestor Framework for Smart Waste Management Efficient closed-form approaches for pose estimation using Sylvester forms World-Value-Action Model: Implicit Planning for Vision-Language-Action Systems A Nonasymptotic Theory of Gain-Dependent Error Dynamics in Behavior Cloning CooperDrive: Enhancing Driving Decisions Through Cooperative Perception SpaceMind: A Modular and Self-Evolving Embodied Vision-Language Agent Framework for Autonomous On-orbit Servicing HiVLA: A Visual-Grounded-Centric Hierarchical Embodied Manipulation System UMI-3D: Extending Universal Manipulation Interface from Vision-Limited to 3D Spatial Perception Towards Multi-Object-Tracking with Radar on a Fast Moving Vehicle: On the Potential of Processing Radar in the Frequency Domain Beyond Conservative Automated Driving in Multi-Agent Scenarios via Coupled Model Predictive Control and Deep Reinforcement Learning Failure Identification in Imitation Learning Via Statistical and Semantic Filtering A Dynamic-Growing Fuzzy-Neuro Controller, Application to a 3PSP Parallel Robot Vision-Language-Action Jump-Starting for Reinforcement Learning Robotic Agents A Mechanistic Analysis of Sim-and-Real Co-Training in Generative Robot Policies ESCAPE: Episodic Spatial Memory and Adaptive Execution Policy for Long-Horizon Mobile Manipulation Evolvable Embodied Agent for Robotic Manipulation via Long Short-Term Reflection and Optimization
A Sliding Mode Controller Based on Timoshenko Beam Theory...
Shifa Sulaiman, Mohammad Gohari, Francesco Schetter, Fanny Ficuc · 2026-01-12 · via cs.RO updates on arXiv.org

Development of dexterous robotic joints is essential for advancing manipulation capabilities in robotic systems. This paper presents the design and implementation of a tendon-driven robotic wrist joint together with an efficient Sliding Mode Controller (SMC) for precise motion control. The wrist mechanism is modeled using a Timoshenko-based approach to accurately capture its kinematic and dynamic properties, which serve as the foundation for tendon force calculations within the controller. The proposed SMC is designed to deliver fast dynamic response and computational efficiency, enabling accurate trajectory tracking under varying operating conditions. The effectiveness of the controller is validated through comparative analyses with existing controllers for similar wrist mechanisms. The proposed SMC demonstrates superior performance in both simulation and experimental studies. The Root Mean Square Error (RMSE) in simulation is approximately 1.67e-2 radians, while experimental validation yields an error of 0.2 radians. Additionally, the controller achieves a settling time of less than 3 seconds and a steady-state error below 1e-1 radians, consistently observed across both simulation and experimental evaluations. Comparative analyses confirm that the developed SMC surpasses alternative control strategies in motion accuracy, rapid convergence, and steady-state precision. This work establishes a foundation for future exploration of tendon-driven wrist mechanisms and control strategies in robotic applications.