Dynamical Obstacle Avoidance of Task- Constrained Mobile Manipulation Using Model Predictive Control

Mecanum wheels can apply a flexible mobility to a mobile robot, in this paper, a mobile manipulation robot is designed with combination of a Mecanum wheeled mobile platform and a 7-degrees of freedom (DoF) robot manipulator. Due to the mechanism of Omni-directional mobility, the Mecanum wheeled robot suffers with slip errors on the free rollers, these errors may be reduced with additional sensors and appropriate feedback control. However, while the mobile platform and the manipulator operate simultaneously, the displacement of the center of gravity of the whole robot increases the complexity to the motion control. To solve this problem, we analyze and model the effect of inconsistency of slippage errors caused by the unbalance of normal force on the wheels, and propose an on-line adaption slippage model for the Mecanum vehicle to generate a better control system to reduce these errors. We proof the effectiveness by using our proposed adaption model and on-line compensation control with experiments.

The problem of door opening is very fundamental for mobile manipulators operating in domestic environments. In order to successfully achieve the door opening task with wheeled mobile redundant manipulators, a manipulability improving scheme is proposed and investigated in this paper. The scheme treats the wheelchair and the manipulator as a whole system and can improve the manipulator's manipulability when opening the door. And thus remedy the manipulator's manipulability decreasing and/or joint variable' abrupt change as well as the workspace limitations during opening the doors. What's more, the control scheme can drive the wheelchair to move according to the end-effector so as not to collide with the door, and can open door smoothly. Firstly, the velocity of the end-effector is generated with the hybrid position/force control for opening doors, and then the coordinated motion control of mobile platform and the manipulator is adopted to drive the whole system moving to a suitable position to open doors successfully. The control scheme can be used by any mobile manipulator that can be velocity controlled. For verifying the performance of the proposed scheme during opening doors, simulations performed on a wheelchair mounted with a 6-DOF robot arm.

A mobile manipulator is a mobile platform with a mounted serial manipulator. A Mobile Manipulator is a system subject to its kinematic restrictions and the degrees of freedom of the manipulator arm mounted on it. These systems combine the advantages of mobile platforms and robotic arms, and reduce their disadvantages. For example, a mobile manipulator has larger working space when it has a mobile platform, as it offers more functionality during operation. For the previously mentioned in this work will be shown the implementation in the robotic simulation software Webots, a mobile manipulator that allows to determine its operation in a virtual environment

Fil: Roberti, Flavio. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - San Juan. Instituto de Automatica. Universidad Nacional de San Juan. Facultad de Ingenieria. Instituto de Automatica; Argentina

The legged mobile manipulator consists of a multi-legged robot mounted with a robotic arm. The advantage of this robotic system is that it has more mobility and manipulability compared to wheeled mobile manipulator. In this work, a legged mobile manipulator is developed for education and research purpose at low cost, which is named as SiMMER (Six-legged Mobile Manipulator for Education and Research). Then, a novel control strategy is proposed for the coordinated movement of all the joints to execute a given task in Cartesian space. Robot Operating System, a Raspberry Pi and two PCA9685 16-Channel 12-bit PWM Servo Motor Driver I2C Modules are used to control the robot. Finally, the control strategy is implemented on a physical prototype. The experimental results show that all the joints are moving as desired, so that the end-effector is able to follow the given trajectory.

The traditional robotic arm control method has strong dependence on the application scenario. To improve the reliability of the mobile robotic arm control when the scene is disturbed, this paper proposes a control method based on an improved proximal policy optimization algorithm. This study researches mobile robotic arms for opening doors. At first, the door handle position is obtained through an image-recognition method based on YOLOv5. Second, the simulation platform CoppeliaSim is used to realize the interaction between the robotic arm and the environment. Third, a control strategy based on a reward function is designed to train the robotic arm and applied to the opening-door task in the real environment. The experimental results show that the proposed method can accelerate the convergence of the training process. Besides, our method can effectively reduce the jitter of the robotic arm and improve the stability of control.

Legged mobile manipulators are receiving much more attention. Mobile platforms can infinitely expand the workspace of robotic arms, providing more possibilities for robot application scenarios. Compared with wheeled mobile manipulators, legged mobile manipulators have higher requirements for cooperative control of legged robots and robotic arms. This work decouples the control of the robotic arm and the legged robot. On the legged robot side, we explicitly estimate the wrench exerted by the robotic arm on the base and bring it into the legged robot’s dynamics, and then use a nonlinear model predictive controller (NMPC) to control the legged robot. On the robotics arm side, we adopt an impedance controller to realize the end-effector’s force control, and the introduction of impedance control has improved the safety and interactivity of legged mobile manipulators. We conducted experiments on physical robot to compare the differences between decoupled control and independent control, and the results show that the stability and robustness of robot systems have improved using decoupled control.

Mobile manipulator combines the mobility of mobile platform and the dexterity of manipulator, which has the great application potential in industry scenarios. In practical applications, efficiently planning a path in a given environment is the main objective, but the high degrees of redundancy, which is caused by the coupling of platform and manipulator, will make the planning problem more challenging. Therefore, the motion planning based on the RRT-GoalBias algorithm and path smoothing is proposed in this paper, where the kinematics of mobile manipulator is modeled, and the constraints of configuration and obstacle avoidance are analyzed. Subsequently, the RRT-GoalBias algorithm is applied and modified to generate an initial path for mobile manipulator in a given site, and a novel post-processing algorithm is proposed to smooth and optimize the initial path. Comparative Simulations are carried out with MATLAB and V-REP to verify the effectiveness of the proposed path planning algorithm for mobile manipulator under the given environment.

Mobile manipulation typically entails the base for mobility, the arm for accurate manipulation, and the camera for perception. The principle of Distant Mobility, Close Grasping(DMCG) is essential for holistic control. We propose Embod-ied Holistic Control for Mobile Manipulation(EHC-MM) with the embodied function of sig( <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\omega$</tex> ): By formulating the DMCG principle as a Quadratic Programming (QP) problem, sig( <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\omega$</tex> ) dynamically balances the robot's emphasis between movement and manipulation with the consideration of the robot's state and environment. In addition, we propose the Monitor-Position-Based Servoing (MPBS) with sig( <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\omega$</tex> ), enabling the tracking of the target during the operation. This approach enables coordinated control among the robot's base, arm, and camera, enhancing task efficiency. Through extensive simulations and real-world experiments, our approach significantly improves both the success rate and efficiency of mobile manipulation tasks, achieving a 95.6% success rate in real-world scenarios and a 52.8% increase in time efficiency.

Performance evaluation of isolated three-phase voltage source inverter with LC filter adopting different MPC methods under various types of load

This study achieved four door operations, namely push-opening, push-closing, pull-opening, and pull-closing movements, using a mobile manipulator consisting of a commercially available arm robot and a mobile robot. We assumed that the arm robot is controlled by position commands at intervals of a few milliseconds, and that the mobile robot is guided by a simple straightforward linear trajectory. Ott, Borst, Bäuml, and Hirzinger proposed a push-opening method using impedance control in a cylindrical coordinate system for the arm robot. With this control, when the mobile robot advances toward and through the door, the arm robot moves passively and properly pushes the door open. However, their method is unsuitable for the above type of robot. Thus, we propose a method with two modifications: the use of admittance control and the improvement of force relaxation by considering a force obtained through a novel force decomposition. Furthermore, the proposed method was demonstrated not only in the push-opening movement but also in the push-closing, pull-opening, and pull-closing movements.

Nowadays, mobile manipulators are increasing its popularity on modern industries due to their ability to enhance process flexibility and performance. Mobile manipulators are a wide field of research and one of the main directions is trying to control the whole system as a single device. In this context, this paper addresses the problem of path planning of the end-effector of a mobile manipulator. The proposed approach is based on the integration of the kinematic chain of both the manipulator and the omni-directional base. At the end, a collision-free path planner for the mobile manipulator in complex and known environments with obstacles using A * is derived.

Aiming at a certain kind of omnidirectional mobile manipulators,which generally consist of an omnidirectional mobile platform driven by wheels and a robot arm,an integrated kinematics model is built based on the mechanical structure and motion properties of the omnidirectional mobile manipulator.In addition,its dynamic model is deduced by Lagrangian formalism.In terms of the proposed models,two tracking controllers are designed subsequently.Stability analyses of the proposed controllers are also given. Especially in the tracking controller based on the dynamic model,the coupling torque between the mobile platform and the robot arm is analyzed quantitatively,and compensated in the tracking controller.Simulation results show the correctness of the proposed models and the effectiveness of the control approaches,and indicate that the research can be a general method for modeling and controlling a certain kind of mobile manipulators.

In this paper, we present a real-time whole-body planner for collision-free legged mobile manipulation. We enforce both self-collision and environment-collision avoidance as soft constraints within a Model Predictive Control (MPC) scheme that solves a multi-contact optimal control problem. By penalizing the signed distances among a set of representative primitive collision bodies, the robot is able to safely execute a variety of dynamic maneuvers while preventing any self-collisions. Moreover, collision-free navigation and manipulation in both static and dynamic environments are made viable through efficient queries of distances and their gradients via a euclidean signed distance field. We demonstrate through a comparative study that our approach only slightly increases the computational complexity of the MPC planning. Finally, we validate the effectiveness of our framework through a set of hardware experiments involving dynamic mobile manipulation tasks with potential collisions, such as locomotion balancing with the swinging arm, weight throwing, and autonomous door opening.

This paper presents a predictive control approach for nonholonomic mobile manipulators that simultaneously ensures precise end-effector trajectory tracking and proactive obstacle avoidance. The proposed method begins with constructing a redundant kinematic model that coordinates all joints through the generalized Jacobian matrix. A model predictive control (MPC) scheme is subsequently developed to achieve millimeter-level end-effector tracking accuracy under ideal conditions. Safety-Critical constraints are integrated into the MPC controller via control barrier functions (CBF), which enforce collision avoidance by predicting and preventing potential violations of minimum safety distances. This integrated approach enables the mobile platform to effectively navigate around obstacles while accurately tracking the end-effector trajectory. Finally, the effectiveness of the coordinated control method is demonstrated through simulations.