Modular reconfigurable manipulators enable quick adaptation and versatility to address different application environments and tailor to the specific requirements of the tasks. Task performance significantly depends on the manipulator’s mounted pose and morphology design, therefore posing the need of methodologies for selecting suitable modular robot configurations and mounted pose that can address the specific task requirements and required performance. Morphological changes in modular robots can be derived through a discrete optimization process that involves the selective addition or removal of modules. In contrast, the adjustment of the mounted pose operates within a continuous space, allowing for smooth and precise alterations in both orientation and position. This work introduces a computational framework that simultaneously optimizes the pose and morphology mounted on modular manipulators. The core of the work is that we design a mapping function that implicitly captures the morphological state of manipulators in the continuous space. This transformation function unifies the optimization of mounted pose and morphology within a continuous space. Furthermore, our optimization framework incorporates a array of performance metrics, such as minimum joint effort and maximum manipulability, and considerations for trajectory execution error and physical and collision constraints. To highlight our method’s benefits, we compare it with previous methods that framed such problems as a combinatorial optimization problem and demonstrate its practicality in selecting the modular robot configuration for executing a drilling task with the CONCERT modular robotic platform.

Wideband spectrum analysis requires high sampling rates, leading to huge data computations for narrow resolution bandwidth (RBW) analysis. This paper presents a weighted overlap-add (WOLA) structure to reduce this complexity of implementation. And WOLA structure has lower computational complexity and better time-frequency resolution than existing efficient structures using the variable bandwidth filter (VBF) or the alternate masking scheme (AMS). When applied to an 8GHz spectrum analysis, the WOLA structure could achieve an instantaneous dynamic range (IDR) of 90dB and an RBW of 229kHz in the numerical simulation.

This paper presents a unified controller for dual-arm robot dynamic multi-object nonprehensile transportation. The controller is composed of time-optimal path parameteri-zation (TOPP) and model predictive control (MPC) and aimed at efficiently and dynamically transporting objects using the dual-arm robot under physical constraints while avoiding the slippage of the objects. A force tracking controller without using the force sensor is also proposed to achieve accurate contact force control between the arms and objects. Experiments on the real robot show the effectiveness of the proposed TOPP-MPC-based controller.