As robots begin to perform jobs autonomously, with minimal or no human intervention, a new challenge arises: robots also need to autonomously detect errors and recover from faults. In this paper, we present a Support Vector Machine (SVM)-based fault diagnosis system for a bio-inspired reconfigurable robot named Scorpio. The diagnosis system needs to detect and classify faults while Scorpio uses its crawling and rolling locomotion modes. Specifically, we classify between faulty and non-faulty conditions by analyzing onboard Inertial Measurement Unit (IMU) sensor data. The data capture nine different locomotion gaits, which include rolling and crawling modes, at three different speeds. Statistical methods are applied to extract features and to reduce the dimensionality of original IMU sensor data features. These statistical features were given as inputs for training and testing. Additionally, the c-Support Vector Classification (c-SVC) and nu-SVC models of SVM, and their fault classification accuracies, were compared. The results show that the proposed SVM approach can be used to autonomously diagnose locomotion gait faults while the reconfigurable robot is in operation.

We have developed a biologically inspired reconfigurable quadruped robot which can perform walking and rolling locomotion and transform between walking and rolling by reconfiguring its legs. This paper presents an approach to control rolling locomotion with the biologically inspired quadruped robot. For controlling rolling locomotion, a controller which can compensate robots energy loss during rolling locomotion is designed based on a dynamic model of the quadruped robot. The dynamic model describes planar rolling locomotion based on an assumption that the quadruped robot does not fall down while rolling and the influences of collision and contact with the ground, and it is applied for computing the mechanical energy and a plant in a numerical simulation. The numerical simulation of rolling locomotion on the flat ground verifies the effectiveness of the proposed controller. The simulation results show that the quadruped robot can perform periodic rolling locomotion with the proposed energy-based controller. In conclusion, it is shown that the proposed control approach is effective in achieving the periodic rolling locomotion on the flat ground. We have developed a biologically inspired reconfigurable quadruped robot which can perform walking and rolling locomotion and transform between walking and rolling by reconfiguring its legs. This paper presents an approach to control rolling locomotion with the biologically inspired quadruped robot. For controlling rolling locomotion, a controller which can compensate robots energy loss during rolling locomotion is designed based on a dynamic model of the quadruped robot. The dynamic model describes planar rolling locomotion based on an assumption that the quadruped robot does not fall down while rolling and the influences of collision and contact with the ground, and it is applied for computing the mechanical energy and a plant in a numerical simulation. The numerical simulation of rolling locomotion on the flat ground verifies the effectiveness of the proposed controller. The simulation results show that the quadruped robot can perform periodic rolling locomotion with the proposed energy-based controller. In conclusion, it is shown that the proposed control approach is effective in achieving the periodic rolling locomotion on the flat ground.

This paper presents an approach to the estimation of a window shape for increasing the adaptability of glass façade-cleaning robots to different buildings. For this approach, a window scanning robot equipped with a 2D laser range scanner installed perpendicularly to a window surface is developed for the testbed, and a method for the window shape estimation is proposed, which consists of the robot’s pose estimation with an extended Kalman filter (EKF) and the loop closure based on the robot’s pose estimated. The effectiveness of the proposed approach is demonstrated through an experiment that is carried out on a window placed on a floor. The experimental results show that the window scanning robot can acquire a window shape, moving on a window surface, and the proposed approach is effective in increasing the accuracy of the window shape estimation.

This study aims to realize rolling locomotion by a multi-legged robot inspired by “wheel spider” in nature. A novel robot mechanism and a strategy for rolling locomotion is proposed in this paper based on motion analysis of wheel spider species in nature. We also present details of a model of a wheel-spider-inspired hexapod robot and design of its controller in realizing rolling locomotion. Results of numerical simulations validated the efficacy of the proposed approach in synthesizing rolling locomotion in a wheel-spider-inspired hexapod robot.