Daily Assistive Modular Robot Design Based on Multi-Objective Black-Box Optimization

TL;DR

This paper presents a modular robot design that can be reconfigured for diverse tasks using multi-objective black-box optimization, enabling personalized and adaptable robotic solutions for daily life support.

Contribution

It introduces a reconfigurable actuator module and an automated configuration method using Tree-structured Parzen Estimator optimization for personalized robot tasks.

Findings

Successfully reconfigured robot for various functions

Minimized torque requirements for target positions

Demonstrated adaptability in daily life tasks

Abstract

The range of robot activities is expanding from industries with fixed environments to diverse and changing environments, such as nursing care support and daily life support. In particular, autonomous construction of robots that are personalized for each user and task is required. Therefore, we develop an actuator module that can be reconfigured to various link configurations, can carry heavy objects using a locking mechanism, and can be easily operated by human teaching using a releasing mechanism. Given multiple target coordinates, a modular robot configuration that satisfies these coordinates and minimizes the required torque is automatically generated by Tree-structured Parzen Estimator (TPE), a type of black-box optimization. Based on the obtained results, we show that the robot can be reconfigured to perform various functions such as moving monitors and lights, serving food, and so on.