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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Seyed Ali Shahzadeh Fazeli Sohrab Allahyari Arman Gholibeikian S. Ali A. Moosavian Dept. of Mechanical Engineering Advanced Robotics & Automated Systems (ARAS) Laboratory Center of Excellence in Robotics & Control K. N. Toosi University of Technology Tehran Iran

ISBN: (数字)9798331529734

ISBN: (纸本)9798331529741

Mecanum wheeled mobile robots have increasingly caught researchers' attention due to their wide range of applications and higher maneuverability. However, their complex structure makes their trajectory tracking and control problem more challenging. This paper presents a cascaded controller for trajectory tracking of a four-wheel Mecanum mobile robot. The cascaded controller consists of a linear time-varying model predictive controller (LTV-MPC) and an inner PID controller. The proposed controller does not require the system's dynamics model. To this end, the linear time-varying error model used to design the MPC is obtained from the robot's kinematics model. The angular velocities obtained from the predictive controller are then mapped into the required commands for the DC motors using a PID controller. The PID controller is fine-tuned considering the motor's dead zone using the Genetic Algorithm. Simulations and experimental results demonstrate the superiority of the cascaded controller over the regular LTV-MPC. The proposed algorithm can also be used for other real-time implementations of robotic tasks.

关键词： Trajectory tracking System dynamics Robot kinematics Predictive models DC motors Angular velocity Real-time systems Mobile robots Voltage control Genetic algorithms

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Neural Lyapunov control for Nonlinear Systems with Unstructured Uncertainties

Neural Lyapunov Control for Nonlinear Systems with Unstructu...

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American control Conference (ACC)

作者： Shiqing Wei Prashanth Krishnamurthy Farshad Khorrami Dept. of ECE Control/Robotics Research Laboratory NYU Tandon School of Engineering Brooklyn NY USA

Stabilizing controller design and region of attraction (RoA) estimation are essential in nonlinear control. Moreover, it is challenging to implement a control Lyapunov function (CLF) in practice when only partial knowledge of the system is available. We propose a learning framework that can synthesize state-feedback controllers and a CLF for control-affine nonlinear systems with unstructured uncertainties. Based on a regularity condition on these uncertainties, we model them as bounded disturbances and prove that a CLF for the nominal system (estimate of the true system) is an input-to-state stable control Lyapunov function (ISS-CLF) for the true system when the CLF’s gradient is bounded. We integrate the robust Lyapunov analysis with the learning of both the control law and CLF. We demonstrate the effectiveness of our learning framework on two examples, such as an inverted pendulum system and a cart-pole system.

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A Passive Mechanical Add-on for Treadmill Exercise (P-MATE) in Stroke Rehabilitation

arXiv

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arXiv 2025年

作者： Beck, Irene L.Y. Hopmans, Belle C. Haanen, Bram Kieft, Levi Vallery, Heike Marchal-Crespo, Laura Poggensee, Katherine L. Dept. of Cognitive Robotics TU Delft Delft Netherlands Dept. of Rehabilitation Medicine Erasmus MC Rotterdam Netherlands Dept. of Biomechanical Engineering TU Delft Delft Netherlands Institute of Automatic Control RWTH Aachen University Aachen Germany

Robotic rehabilitation can deliver high-dose gait therapy and improve motor function after a stroke. However, for many devices, high costs and lengthy setup times limit clinical adoption. Thus, we designed, built, and evaluated the Passive Mechanical Add-on for Treadmill Exercise (P-MATE), a low-cost passive end-effector add-on for treadmills that couples the movement of the paretic and non-paretic legs via a reciprocating system of elastic cables and pulleys. Two human-device mechanical interfaces were designed to attach the elastic cables to the user. The P-MATE and two interface prototypes were tested with a physical therapist and eight unimpaired participants. Biomechanical data, including kinematics and interaction forces, were collected alongside standardized questionnaires to assess usability and user experience. Both interfaces were quick and easy to attach, though user experience differed, highlighting the need for personalization. We also identified areas for future improvement, including pretension adjustments, tendon derailing prevention, and understanding long-term impacts on user gait. Our preliminary findings underline the potential of the P-MATE to provide effective, accessible, and sustainable stroke gait rehabilitation. © 2025, CC BY-NC-ND.

关键词： End effectors

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Adaptive Output Regulation of MIMO LTI Systems with Unmodeled Input Dynamics

Adaptive Output Regulation of MIMO LTI Systems with Unmodele...

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IEEE Conference on Decision and control

作者： Oleg Borisov Alberto Isidori Anton Pyrkin Faculty of Control Systems and Robotics ITMO University St. Petersburg Russia Dept. of Computer Control and Management Engineering University “Sapienza” Rome Italy

This paper addresses the problem of adaptive output regulation of a minimum-phase MIMO LTI system in the presence of un-modeled (fast) input dynamics. The adoption of a post-processing tunable internal model makes it possible to implement standard methods for the analysis of two-time-scale systems. The proposed adaptation law guarantees, under suitable hypotheses, convergence to zero of the regulation error as well as of the parameter estimation error.

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Robust Prescribed-Time Practical Tracking and Disturbance Attenuation for Flexible-Joint Manipulators with Input Unmodeled Dynamics

Robust Prescribed-Time Practical Tracking and Disturbance At...

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European control Conference (ECC)

作者： P. Krishnamurthy F. Khorrami A. Tzes Dept. of ECE NYU Tandon School of Engineering Control/Robotics Research Laboratory (CRRL) Brooklyn NY USA Dept. of ECE NYU Abu Dhabi UAE

A prescribed-time robust nonlinear controller for multi-link robotic manipulators with flexible joints and uncertain input unmodeled dynamics is considered. The controller achieves regulation of the tracking error to within an arbitrarily specified neighborhood of zero (i.e., “practical” tracking) within an arbitrary time interval specified by the control designer. The controller is robust to disturbance torques as well as uncertainties in parameters of the robotic manipulator in addition to uncertain actuator dynamics in the form of input unmodeled dynamics. Time-varying control gains in a vector backstepping approach along with a dynamic scaling based approach to handle input unmodeled dynamics are used to enforce convergence of the tracking error to within the specified neighborhood within the specified time interval. Simulation studies for a two-link manipulator with flexible joints and input unmodeled dynamics are presented to demonstrate the efficacy of the proposed controller design.

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Multi-aspect Optimal Sliding Mode controller for a Mecanum Wheeled Robot

Multi-aspect Optimal Sliding Mode Controller for a Mecanum W...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Sohrab Allahyari Hamid Rahmanei S. Ali A. Moosavian Dept. of Mechanical Engineering Center of Excellence in Robotics & Control Advanced Robotics & Automated Systems (ARAS) Laboratory K. N. Toosi University of Technology Tehran

Four-wheel drive Mecanum robots have gained attention due to their ability to move in all directions, which allows them to work in tight and complex environments. For this reason, ensuring precise control of these robots along predefined trajectories is crucial. This work presents a comparative study on the effects of parametric uncertainties, external disturbances, measurement noises, and initial deviations on the trajectory-tracking performance of a 4-wheel drive Mecanum robot. First, the kinematic and kinetic models of the Mecanum robot are introduced. Then, the integral sliding mode control is designed, and proof of stability is provided. In addition, we explore other control strategies, including PID, feedback linearization, sliding mode, and adaptive sliding mode control, that are designed for this robot. Furthermore, the particle swarm optimization algorithm is hired for the controllers with a cost function as the total sum of average error, maximum error, and final error. Optimization has been done on all controllers to compare the results fairly. To appraise the effectiveness of the proposed control optimization methods, simulations are carried out in MATLAB/Simulink. The results reveal that the proposed ISMC method performs best in both defined scenarios compared to other controllers. However, it must be noted that the ISMC controller exhibits limitations when facing significant uncertainties in the dynamic model. This study underscores the effectiveness of our proposed control method and provides valuable insights into the practical implementation controller for the Mecanum robot in real-world applications.

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Parameter Adjustments in POMDP-Based Trajectory Planning for Unsignalized Intersections

arXiv

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arXiv 2024年

作者： Kollarčík, Adam Hanzálek, Zdeněk Dept. of Control Engineering Faculty of Electrical Engineering Czech Technical University Prague Czech Republic Czech Institute of Informatics Robotics and Cybernetics Czech Technical University Prague Czech Republic

This paper investigates the problem of trajectory planning for autonomous vehicles at unsignalized intersections, specifically focusing on scenarios where the vehicle lacks the right of way and yet must cross safely. To address this issue, we have employed a method based on the Partially Observable Markov Decision Processes (POMDPs) framework designed for planning under uncertainty. The method utilizes the Adaptive Belief Tree (ABT) algorithm as an approximate solver for the POMDPs. We outline the POMDP formulation, beginning with discretizing the intersection’s topology. Additionally, we present a dynamics model for the prediction of the evolving states of vehicles, such as their position and velocity. Using an observation model, we also describe the connection of those states with the imperfect (noisy) available measurements. Our results confirmed that the method is able to plan collision-free trajectories in a series of simulations utilizing real-world traffic data from aerial footage of two distinct intersections. Furthermore, we studied the impact of parameter adjustments of the ABT algorithm on the method’s performance. This provides guidance in determining reasonable parameter settings, which is valuable for future method applications. © 2024, CC BY-NC-ND.

关键词： Markov processes

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Delayed dynamic-feedback controller design for multi-frequency vibration suppression

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IFAC-PapersOnLine 2024年第27期58卷 196-201页

作者： Adrian Saldanha Adam Peichl Wim Michiels Tomas Vyhlidal Department of Computer Science KU Leuven Celestijnenlaan 200A 3001 Leuven Belgium Dept. Instrumentation and Control Engineering Faculty of Mechanical Engineering and Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague 6 Czechia

We present a methodology for designing a dynamic controller with delayed output feedback for achieving non-collocated vibration suppression with a focus on the multi-frequency case. To synthesize the delay-based controller, we first remodel the system of equations as a delay-differential algebraic equation (DDAE) in such a way that existing tools for design of a static output feedback controller can be easily adapted. The problem of achieving non-collocated vibration suppression with sufficient damping is formulated as a constrained optimization problem of minimizing the spectral abscissa in the presence of zero-location constraints, with the constraints exhibiting polynomial dependence on its parameters. We transform the problem into an unconstrained one using elimination, following which we solve the resulting non-convex, non-smooth optimization problem.

关键词： vibration suppression time-delay DDAE

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POMDP-Based Trajectory Planning for On-Ramp Highway Merging

arXiv

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arXiv 2024年

This paper addresses the trajectory planning problem for automated vehicle on-ramp highway merging. To tackle this challenge, we extend our previous work on trajectory planning at unsignalized intersections using Partially Observable Markov Decision Processes (POMDPs). The method utilizes the Adaptive Belief Tree (ABT) algorithm, an approximate sampling-based approach to solve POMDPs efficiently. We outline the POMDP formulation process, beginning with discretizing the highway topology to reduce problem complexity. Additionally, we describe the dynamics and measurement models used to predict future states and establish the relationship between available noisy measurements and predictions. Building on our previous work, the dynamics model is expanded to account for lateral movements necessary for lane changes during the merging process. We also define the reward function, which serves as the primary mechanism for specifying the desired behavior of the automated vehicle, combining multiple goals such as avoiding collisions or maintaining appropriate velocity. Our simulation results, conducted on three scenarios based on real-life traffic data from German highways, demonstrate the method’s ability to generate safe, collision-free, and efficient merging trajectories. This work shows the versatility of this POMDP-based approach in tackling various automated driving problems. © 2024, CC BY-NC-ND.

关键词： Markov processes

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Fuzzy controlled Adaptive Follow the Gap Obstacle Avoidance Algorithm 21

Fuzzy Controlled Adaptive Follow the Gap Obstacle Avoidance ...

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Proceedings of the 7th International Conference on robotics and Artificial Intelligence

作者： Bilal Yucel Abdurrahman Yilmaz Osman Ervan Hakan Temeltas Control and Automation Engineering Dept. Robotics Laboratory Istanbul Technical University Turkey

ISBN: (纸本)9781450385855

Follow the Gap Method (FGM) and Improved Follow the Gap Method (FGM-I) are geometric obstacle avoidance algorithms for navigation. In these methods, the vehicle detects the gaps around the object and navigates to the midpoint of the optimal gap calculated according to a defined function. One missing point of these algorithms is failure to the goal point when there is an obstacle near to it. Another drawback is that early consideration of obstacles causes long trajectories. In this paper, Adaptive Follow the Gap (A-FGM) is presented to overcome these two points. In A-FGM, a fuzzy controlled evaluation radius is set and only obstacles within this region are included in the evaluation. A differential drive robot is used in simulations and results show that A-FGM increases the success rate of reaching the goal and efficiency of previous algorithms. The source code of the developed approach is shared on GitHub 1.

关键词： Mobile Robots Fuzzy control Path Planning Robot Navigation Adaptive control Obstacle Avoidance

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