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Traditional coordinated motion planning schemes for mobile robot manipulators are primarily designed at the velocity level, which limits their applicability to acceleration-oriented systems. To address this limitation, this paper proposes, for the first time, a kinematic model and a trajectory tracking scheme for a two-wheeled mobile robot manipulator (TWMRM) at the acceleration level. This innovation enables the TWMRM system to achieve improved precision and stability under complex dynamic conditions. Compared to velocity-level approaches, the proposed acceleration-level scheme is applicable to both acceleration-oriented and velocity-oriented mobile robot manipulators, offering a broader range of applications. To verify the proposed approach, trajectory-tracking simulations show that the TWMRM’s end-effector closely follows the desired trajectory, with position errors on the order of ${10}^{-7}$ and no divergence issue. Additionally, practical experiments confirm the feasibility of the acceleration-level kinematic model and trajectory tracking scheme for real-world applications.

Autonomous multi-robot optical inspection systems are increasingly applied for obtaining inline measurements in process monitoring and quality control. Numerous methods for path planning and robotic coordination have been developed for static and dynamic environments and applied to different fields. However, these approaches may not work for the autonomous multi-robot optical inspection system due to fast computation requirements of inline optimization, unique characteristics on robotic end-effector orientations, and complex large-scale free-form product surfaces. This paper proposes a novel task allocation methodology for coordinated motion planning of multi-robot inspection. Specifically, (1) a local robust inspection task allocation is proposed to achieve efficient and well-balanced measurement assignment among robots; (2) collision-free path planning and coordinated motion planning are developed via dynamic searching in robotic coordinate space and perturbation of probe poses or local paths in the conflicting robots. A case study shows that the proposed approach can mitigate the risk of collisions between robots and environments, resolve conflicts among robots, and reduce the inspection cycle time significantly and consistently. [ABSTRACT FROM AUTHOR]

The mobile redundant manipulator (MRM) shows a great advantage in its in situ high-precision assembly field of large complex components (LCCs), due to its high mobility, flexibility, and dexterity. However, the redundancy degree of freedom of the MRM makes its motion planning difficult. Furthermore, the inconsistent stiffness of different configurations of the MRM may cause poor manufacturing quality. Therefore, it is necessary to optimize the process pose with better stiffness performance during the motion planning. This paper proposes an integrated motion planning method to optimize the kinematics and stiffness performance of the MRM for LCCs' assembly and process. In addition to the multiple constraints such as joint angle, joint velocity, and singular posture avoidance, the time-varying normal direction of LCCs and the stiffness performance of MRM's configuration are considered in the optimization algorithm, by calculating the Roll-Pitch-Yaw angles (RPY angles) at each moment and defining the stiffness index. The simulation results illustrated that the proposed method can effectively plan the desired trajectories for the mobile platform and the manipulator separately. Compared with the non-stiffness constraint planning method, the proposed method enjoys superiority on stiffness performance. [ABSTRACT FROM AUTHOR]

The underwater vehicle-manipulator systems (UVMS) face significant challenges in trajectory tracking and motion planning because of external disturbance (current and payload) and kinematic redundancy. Former algorithms can finish the tracking of end-effector (EE) and free of singularity redundancy solution alone. However, only a few analytical studies have been conducted on coordinated motion planning of UVMS considering the dynamics controller. This article introduces a combined dynamics and kinematics networked fuzzy task priority motion planning method to solve the above problems. It avoids the assumption of perfect dynamic control. Firstly, to eliminate the kinematics error, a dynamic transformation method from joint space to task space is proposed. Without chattering, an outer loop sliding mode controller is designed for tracking EE's trajectory. Further, to ensure the underwater vehicle' posture stability and joint constraint, a task priority frame with kinematics error is used to planning the coordinated motion of UVMS, in which the posture and joint limits map into the null space of prioritized tasks, and weight gains are adopted to guarantee orthogonality of secondary tasks. On top of that, the gain weighted are updated by the networked fuzzy logic. The proposed algorithm achieves better coordinated motion planning and tracking performance. Effectiveness is validated by numerical simulation. [ABSTRACT FROM AUTHOR]

We develop constant-factor approximation algorithms for minimizing the execution time of a coordinated parallel motion plan for a relatively dense swarm of homogeneous robots in the absence of obstacles. In our first model, each robot has a specified start and destination on the square grid, and in each round of coordinated parallel motion, every robot can move to any adjacent position that is either empty or simultaneously being vacated by another robot. In this model, our algorithm achieves constant stretch factor: if every robot starts at distance at most d from its destination, then the total duration of the overall schedule is O(d), which is optimal up to constant factors. Our result holds for distinguished robots (each robot has a specific destination), identical (unlabeled) robots, and most generally, classes of different robot types (where each destination specifies a required type of robot). We also show that finding the optimal coordinated parallel motion plan is NP-hard, justifying approximation algorithms. In our second model, each robot is a unit-radius disk in the plane, and robots can translate continuously in parallel subject to not intersecting, i.e., having disk centers at L2-distance at least 2. We prove the same result--constant-factor approximation algorithm to minimizing execution time via constant stretch factor---when the pairwise L∞ -distance between disk centers is at least 2√ 2 = 2.8284 . . . . On the other hand, for N densely packed disks at distance at most 2 + δ for a sufficiently small δ > 0, we prove that a stretch factor of Ω(N1/4) is sometimes necessary (when densely packed), while a stretch factor of O (N1/2) is always possible. [ABSTRACT FROM AUTHOR]

Application of the multi-arm space robot will be more effective than single arm especially when the target is tumbling. This paper investigates the application of particle swarm optimization (PSO) strategy to coordinated trajectory planning of the dual-arm space robot in free-floating mode. In order to overcome the dynamics singularities issue, the direct kinematics equations in conjunction with constrained PSO are employed for coordinated trajectory planning of dual-arm space robot. The joint trajectories are parametrized with Bézier curve to simplify the calculation. Constrained PSO scheme with adaptive inertia weight is implemented to find the optimal solution of joint trajectories while specific objectives and imposed constraints are satisfied. The proposed method is not sensitive to the singularity issue due to the application of forward kinematic equations. Simulation results are presented for coordinated trajectory planning of two kinematically redundant manipulators mounted on a free-floating spacecraft and demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

We introduce the use of hierarchical clustering for relaxed deterministic coordination and control of multiple robots. Traditionally, an unsupervised learning method, hierarchical clustering offers a formalism for identifying and representing spatially cohesive and segregated robot groups at different resolutions by relating the continuous space of configurations to the combinatorial space of trees. We formalize and exploit this relation, developing computationally effective reactive algorithms for navigating through the combinatorial space in concert with geometric realizations for a particular choice of the hierarchical clustering method. These constructions yield computationally effective vector field planners for both hierarchically invariant as well as transitional navigation in the configuration space. We apply these methods to the centralized coordination and control of $n$ perfectly sensed and actuated Euclidean spheres in a $d$-dimensional ambient space (for arbitrary $n$ and $d$). Given a desired configuration supporting a desired hierarchy, we construct a hybrid controller that is quadratic in $n$ and algebraic in $d$ and prove that its execution brings all but a measure zero set of initial configurations to the desired goal, with the guarantee of no collisions along the way. [ABSTRACT FROM PUBLISHER]

In order to resolve the redundancy of a wheeled mobile redundant manipulator comprising a two-wheel-drive mobile platform and a 6-degree-of-freedom manipulator, a physical-limits-constrained (PLC) minimum velocity norm (MVN) coordinating scheme (termed as PLC-MVN-C scheme) is proposed and investigated. Such a scheme can not only coordinate the mobile platform and the manipulator to fulfill the end-effector task and to achieve the desired optimal index (i.e., minimizing the norm of the rotational velocities of the wheels and the joint velocities of the manipulator) but also consider the physical limits of the robot (i.e., the joint-angle limits and joint-velocity limits of the manipulator as well as the rotational velocity limits of the wheels). The scheme is then reformulated as a quadratic program (QP) subject to equality and bound constraints, and is solved by a discrete QP solver, i.e., a numerical algorithm based on piecewise-linear projection equations (PLPE). Simulation results substantiate the efficacy and accuracy of such a PLC-MVN-C scheme and the corresponding discrete PLPE-based QP solver. [ABSTRACT FROM AUTHOR]