This study aims to create an on-demand intelligent space using a detachable arm that can be installed only when needed. To enable stable task performance in various environments, this study proposes a method to co-optimize the arm's placement and mounting surface shape. This is achieved by solving a single nonlinear optimization problem that integrates four key requirements: geometric conditions, mechanical stability, design of the mounting surface shape, and the trade-off between stability and space-saving. To physically realize the diverse shapes derived from this optimization, a modular outrigger mechanism is designed. Experiments with a real robot demonstrated that the system adaptively generates the minimum necessary mounting surface for different task requirements, such as operating in confined spaces or withstanding large forces.

In this paper, a sufficient condition for the small-signal stability of power systems with lossy transmission lines, virtual synchronous generator (VSG) model grid-forming inverters and grid-following inverters is derived using the Integral Quadratic Constraints (IQC) framework. The analysis employs two system representations, referred to as the forward and inverse systems. The resulting stability condition comprises a circle criterion for the forward system at the DC gain and a phase condition for both systems over the remaining frequency range. Numerical results demonstrate that the proposed condition accurately captures the stability boundary when transmission line resistance is small.

Autonomous mobile robots employ various cooperative control methods, including consensus control, coverage control, and formation control, to achieve global objectives. However, a key issue is that only the robots themselves adapt to control tasks based on environmental conditions and cyber-physical constraints. To address this limitation, this paper proposes a novel human-robot control architecture that leverages human-guided individual task assignment via large language models to assign control roles to specific robots. A proof of concept for the proposed control architecture is demonstrated through simulations and voice-prompt-based experiments.

This study aims to solve the sequential execution bottleneck caused by a single general-purpose robot performing multiple tasks. In our approach, the robot achieves parallelization by delegating tasks to detachable arms, which can be placed in and retrieved from the environment as needed. Considering the overhead of arm placement and retrieval, we define the “Task Delegation Scheduling Problem”, where the system selects whether the robot executes a task itself or delegates it to an arm. Through simulations, we present guidelines for system design and task operation and analyze the mechanisms of optimal strategies based on task structure. Furthermore, we conduct a proof-of-concept with a real robot and discuss the application scope of this method.