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arXiv 2024年

作者： Ly, Kim Tien Lu, Kai Havoutis, Ioannis Oxford Robotics Institute University of Oxford United Kingdom Department of Computer Science University of Oxford United Kingdom

We introduce an interactive LLM-based framework designed to enhance the autonomy and robustness of domestic robots, targeting embodied intelligence. Our approach reduces reliance on large-scale data and incorporates a robot-agnostic pipeline that embodies an LLM. Our framework, InteLiPlan, ensures that the LLM’s decision-making capabilities are effectively aligned with robotic functions, enhancing operational robustness and adaptability, while our human-in-the-loop mechanism allows for real-time human intervention when user instruction is required. We evaluate our method in both simulation and on the real Toyota Human Support Robot (HSR). Our method achieves a 93% success rate in the ‘fetch me’ task completion with failure recovery, highlighting its capability in both failure reasoning and task planning. InteLiPlan achieves comparable performance to state-of-the-art large-scale LLM-based robotics planners, while using only real-time onboard computing. More information about InteLiPlan can be found at the project website: https://***/InteLiPlan. Copyright © 2024, The Authors. All rights reserved.

关键词： Human robot interaction

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A CBF-Adaptive Control Architecture for Visual Navigation for UAV in the Presence of Uncertainties

A CBF-Adaptive Control Architecture for Visual Navigation fo...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Viswa Narayanan Sankaranarayanan Akshit Saradagi Sumeet Satpute George Nikolakopoulos Robotics and Artificial Intelligence Group of the Department of Computer Science Electrical and Space Engineering Luleå University of Technology Sweden

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In this article, we propose a control solution for the safe transfer of a quadrotor UAV between two surface robots positioning itself only using the visual features on the surface robots, which enforces safety constraints for precise landing and visual locking, in the presence of modeling uncertainties and external disturbances. The controller handles the ascending and descending phases of the navigation using a visual locking control barrier function (VCBF) and a parametrizable switching descending CBF (DCBF) respectively, eliminating the need for an external planner. The control scheme has a backstepping approach for the position controller with the CBF filter acting on the position kinematics to produce a filtered virtual velocity control input, which an adaptive controller tracks to overcome modeling uncertainties and external disturbances. The experimental validation is carried out with a UAV that navigates from the base to the target using an RGB camera.

关键词： Visualization Uncertainty Target tracking Navigation Velocity control Robot vision systems Switches

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Extremely Weak Feedback Method for Controlling Chaotic Resonance

Extremely Weak Feedback Method for Controlling Chaotic Reson...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Iinuma, Takahiro Ebato, Yudai Nobukawa, Sou Tran, Anh Tu Wagatsuma, Nobuhiko Inagaki, Keiichiro Doho, Hirotaka Yamanishi, Teruya Nishimura, Haruhiko Graduate School of Information and Computer Science Chiba Institute of Technology Chiba Japan Chiba Institute of Technology Department of Computer Science Japan Toho University Faculty of Science Department of Information Science Chiba Japan Chubu University Department of Artificial Intelligence and Robotics Aichi Japan Kouchi University Faculty of Education Teacher Training Division Kochi Japan Osaka Seikei University Faculty of Data Science Osaka Japan Yamato University Faculty of Informatics Osaka Japan

ISBN: (纸本)9798350337020

Chaotic resonance, resembling stochastic resonance, is induced by internal fluctuations (i.e., chaos). This phenomenon has been observed in numerous systems. The most representative form of chaotic resonance is the synchronization with respect to weak applied signals under chaos-chaos intermittency, where a chaotic orbit moves among multiple attractors. Chaotic resonance exhibits higher sensitivity than stochastic resonance, but its engineering applications are limited by concerns such as the requirement to adjust the state of chaos by internal system parameters to induce chaotic resonance rather than the external noise strength. However, achieving this adjustment is challenging, especially in biological systems. Therefore, to handle this limitation, we proposed a novel double-Gaussian-filtered reduced region of orbit (RRO) method (called the DG-RRO method) for obtaining perturbed feedback signals lower than the conventional RRO method. This DG-RRO feedback signal is determined by the inverse sign of the map function and double-Gaussian filters around the local maximum/minimum values of the map. Because of its fine local specification, the DG-RRO feedback signal induces a chaotic resonance by one-third the feedback strength of the conventional signal. This method may pave the way for using chaotic resonance in engineering applications. © 2023 IEEE.

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Toward Life-Long Creative Problem Solving: Using World Models for Increased Performance in Novelty Resolution 13

Toward Life-Long Creative Problem Solving: Using World Model...

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13th International Conference on Computational Creativity, ICCC 2022

作者： Gizzi, Evana Lin, Wo Wei Castro, Mateo Guaman Harvey, Ethan Sinapov, Jivko Department of Computer Science Tufts University MA United States Department of Electrical and Computer Engineering Tufts University MA United States The Robotics Institute Carnegie Mellon University PA United States

ISBN: (纸本)9789895416042

Creative problem solving (CPS) is a skill which enables innovation, often times through repeated exploration of an agent’s world. In this work, we investigate methods for life-long creative problem solving (LLCPS), with the goal of increasing CPS capability over time. We develop two world models to facilitate LLCPS which use sub-symbolic action and object information to predict symbolic meta-outcomes of actions. We experiment with three CPS scenarios run sequentially and in simulation. Results suggest that LLCPS is possible through the use of a world model, which can be trained on CPS exploration trials, and used to guide future CPS exploration. © 2022 Proceedings of the 13th International Conference on Computational Creativity, ICCC 2022. All rights reserved.

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One-Shot Gesture Recognition for Underwater Diver-To-Robot Communication

arXiv

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arXiv 2025年

作者： Joshi, Rishikesh Sattar, Junaed Department of Computer Science and Engineering Minnesota Robotics Institute University of Minnesota – Twin Cities MinneapolisMN United States

Reliable human-robot communication is essential for effective underwater human-robot interaction (U-HRI), yet traditional methods such as acoustic signaling and predefined gesture-based models suffer from limitations in adaptability and robustness. In this work, we propose One-Shot Gesture Recognition (OSG), a novel method that enables real-time, pose-based, temporal gesture recognition underwater from a single demonstration, eliminating the need for extensive dataset collection or model retraining. OSG leverages shape-based classification techniques, including Hu moments, Zernike moments, and Fourier descriptors, to robustly recognize gestures in visually-challenging underwater environments. Our system achieves high accuracy on real-world underwater video data and operates efficiently on embedded hardware commonly found on autonomous underwater robots (AUVs), demonstrating its feasibility for deployment on-board robots. Compared to deep learning approaches, OSG is lightweight, computationally efficient, and highly adaptable, making it ideal for diver-to-robot communication. We evaluate OSG’s performance on an augmented gesture dataset and real-world underwater video data, comparing its accuracy against deep learning methods. Our results show OSG’s potential to enhance U-HRI by enabling the immediate deployment of user-defined gestures without the constraints of predefined gesture languages. Copyright © 2025, The Authors. All rights reserved.

关键词： Human robot interaction

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Control Synthesis Problem of Traffic Flow in Urban Network

Control Synthesis Problem of Traffic Flow in Urban Network

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Elena Sofronova Askhat Diveev Department of Robotics Control Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences Moscow Russia

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

The paper deals with the problem of traffic flow control in the urban road networks. The control is performed by traffic lights at intersections. The statement of the optimal control problem is given. A model-based approach is applied. The mathematical model of traffic flow based on the theory of controlled networks is used. A quality criterion is set. It is pointed out that a feature of the control of this object is its cyclical nature. Control is repeated at a certain time interval, which is called a control cycle. The duration of traffic light phases is considered as control. The phases switch sequentially in a certain order. Additional constraints are given that must be taken into account when choosing phase duration. As a result of solution of the optimal control problem the coordination plan for traffic lights is obtained. Coordination plan is cyclically repeated. The control synthesis problem is formulated that accounts for change in initial state. It is proposed to solve the control synthesis problem as a problem of selecting an optimal coordination plan from a set of plans calculated in advance for various initial flow states and model parameters.

关键词： Roads Decision making Optimal control Machine learning Switches Mathematical models Information technology Optimization

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A CBF-Adaptive Control Architecture for Visual Navigation for UAV in the Presence of Uncertainties

arXiv

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arXiv 2024年

作者： Sankaranarayanan, Viswa Narayanan Saradagi, Akshit Satpute, Sumeet Nikolakopoulos, George Robotics and Artificial Intelligence Group The Department of Computer Science Electrical and Space Engineering Luleå University of Technology Sweden

In this article, we propose a control solution for the safe transfer of a quadrotor UAV between two surface robots positioning itself only using the visual features on the surface robots, which enforces safety constraints for precise landing and visual locking, in the presence of modeling uncertainties and external disturbances. The controller handles the ascending and descending phases of the navigation using a visual locking control barrier function (VCBF) and a parametrizable switching descending CBF (DCBF) respectively, eliminating the need for an external planner. The control scheme has a backstepping approach for the position controller with the CBF filter acting on the position kinematics to produce a filtered virtual velocity control input, which is tracked by an adaptive controller to overcome modeling uncertainties and external disturbances. The experimental validation is carried out with a UAV that navigates from the base to the target using an RGB camera. © 2024, CC BY-NC-ND.

关键词： Unmanned aerial vehicles (UAV)

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V3D-SLAM: Robust RGB-D SLAM in Dynamic Environments with 3D Semantic Geometry Voting

V3D-SLAM: Robust RGB-D SLAM in Dynamic Environments with 3D ...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Tuan Dang Khang Nguyen Manfred Huber Department of Computer Science and Engineering Learning and Adaptive Robotics Laboratory University of Texas at Arlington Arlington TX USA

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Simultaneous localization and mapping (SLAM) in highly dynamic environments is challenging due to the correlation complexity between moving objects and the camera pose. Many methods have been proposed to deal with this problem; however, the moving properties of dynamic objects with a moving camera remain unclear. Therefore, to improve SLAM’s performance, minimizing disruptive events of moving objects with a physical understanding of 3D shapes and dynamics of objects is needed. In this paper, we propose a robust method, V3D-SLAM, to remove moving objects via two lightweight reevaluation stages, including identifying potentially moving and static objects using a spatial-reasoned Hough voting mechanism and refining static objects by detecting dynamic noise caused by intra-object motions using Chamfer distances as similarity measurements. Through our experiment on the TUM RGB-D benchmark on dynamic sequences with ground-truth camera trajectories, the results show that our methods outperform most other recent state-of-the-art SLAM methods. Our source code is available at https://***/tuantdang/v3d-slam.

关键词： Simultaneous localization and mapping Three-dimensional displays Source coding Dynamics Noise Benchmark testing Cameras Feature extraction Trajectory Object recognition

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Task Constraint-Guided Inverse Reinforcement Learning (TC-IRL) in Human-Robot Collaborative Assembly

Task Constraint-Guided Inverse Reinforcement Learning (TC-IR...

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IEEE Workshop on Advanced robotics and its Social Impacts, ARSO

作者： Yi Chen Weitian Wang Yunyi Jia ABB Robotics USA Department of Computer Science Montclair State University USA Department of Automotive Engineering Clemson University USA

ISBN: (数字)9798350344639

ISBN: (纸本)9798350344646

Collaborative robots transit from the traditional robot-in-a-cell scenarios to a human-robot-shared workspace. This demands robots to better understand their human partners and then assist them. Existing robot learning from demonstration work mainly focuses on enabling robots to repeat human demonstrated tasks alone and usually require significant training efforts but have limited scalability to new tasks. This paper proposes a new task constraint-guided inverse reinforcement learning (TC-IRL) approach to learn assembly tasks from human demonstrations with significantly reduced state and action space (leading to less training data requirement) and computational efforts (landing to better real-time performance) than the conventional IRL. The TC-IRL is also extended to new geometric-scaled tasks to generate robot assistance to human in collaborative assembly. The proposed approaches are validated and evaluated through human-robot collaborative assembly experiments.

关键词： Training Service robots Scalability Training data Reinforcement learning Robot sensing systems Sensors

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Problem of Optimal Area Monitoring and Universal Motion Stabilisation System for its Practical Realisation

Problem of Optimal Area Monitoring and Universal Motion Stab...

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Askhat Diveev Elena Sofronova Department of Robotics Control Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences Moscow Russia

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

The area monitoring problem is considered as optimization task. The problem belongs to the class of global optimization. First, the problem of finding optimal trajectories is solved so that the control objects, when moving along these trajectories, observe the entire area, do not collide with each other and do not violate phase constraints. One of the main quality criteria when searching for trajectories is their minimum total length, and the closeness of the trajectory lengths of each control object. Subsequently, the optimal control problem is solved in order to ensure the movement of the object along the obtained optimal trajectory. To solve the problem in class of implemented in real object control functions the stabilisation system of control object motion along a given trajectory is synthesized. When solving the optimal control problem, the same criteria are considered as when finding optimal trajectories, with the addition of the accuracy of passing points on trajectories. An illustrative example of solving the optimal area monitoring problem by two quadcopters with one circular phase constraint is provided. Symbolic regression is employed to synthesise a system for stabilising the movement of an object along the optimal trajectory.

关键词： Accuracy Perturbation methods Optimal control Search problems Trajectory Feedback control Information technology Monitoring Optimization Quadrotors

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