A Swarm Robotic Approach to Inspection of 2.5 D Surfaces in Orbit

Robotic inspection offers a robust, scalable, and flexible alternative to deploying fixed sensor networks or humaninspectors. While prior work has mostly focused on single robot inspections, this work studies the deployment of a swarm ofinspecting robots on a simplified surface of an in-orbit infrastructure. The robots look for points of mechanical failure and inspectthe surface by assessing propagating vibration signals. In particular, they measure the magnitude of acceleration they sense ateach location on the surface. Our choice for sensing and analyzing vibration signals is supported by the established position ofvibration analysis methods in industrial infrastructure health assessment. We perform simulation studies in Webots, a physicsbased robotic simulator, and present a distributed inspection algorithm based on bio-inspired particle swarm optimization andevolutionary algorithm niching techniques to collectively localize an a priori unknown number of mechanical failure points. Toperform the vibration analysis and obtain realistic acceleration data, we use the ANSYS multi-physics simulation software andmodel mechanical failure points as vibration sources on the surface. We deploy a robot swarm comprising eight robots of 10-cmsize that use a bio-inspired inchworming locomotion pattern. The swarm is deployed on 2.5D (that is curved 2D) cylindricalsurfaces with and without obstacles to investigate the robustness of the algorithm in environments with varying geometric complexity. We study three performance metrics: (1) proximity of the localized sources to their ground truth locations, (2) time tolocalize each source, and (3) time to finish the inspection task given an 80% surface coverage threshold. Our results show thatthe robots accurately localize all the failure sources and reach the coverage threshold required to complete the inspection. Thiswork demonstrates the viability of deploying robot swarms for inspection of potentially complex 3D environments.<br/

A Swarm Robotic Approach to Inspection of 2.5 D Surfaces in Orbit

Robotic inspection offers a robust, scalable, and flexible alternative to deploying fixed sensor networks or humaninspectors. While prior work has mostly focused on single robot inspections, this work studies the deployment of a swarm ofinspecting robots on a simplified surface of an in-orbit infrastructure. The robots look for points of mechanical failure and inspectthe surface by assessing propagating vibration signals. In particular, they measure the magnitude of acceleration they sense ateach location on the surface. Our choice for sensing and analyzing vibration signals is supported by the established position ofvibration analysis methods in industrial infrastructure health assessment. We perform simulation studies in Webots, a physicsbased robotic simulator, and present a distributed inspection algorithm based on bio-inspired particle swarm optimization andevolutionary algorithm niching techniques to collectively localize an a priori unknown number of mechanical failure points. Toperform the vibration analysis and obtain realistic acceleration data, we use the ANSYS multi-physics simulation software andmodel mechanical failure points as vibration sources on the surface. We deploy a robot swarm comprising eight robots of 10-cmsize that use a bio-inspired inchworming locomotion pattern. The swarm is deployed on 2.5D (that is curved 2D) cylindricalsurfaces with and without obstacles to investigate the robustness of the algorithm in environments with varying geometric complexity. We study three performance metrics: (1) proximity of the localized sources to their ground truth locations, (2) time tolocalize each source, and (3) time to finish the inspection task given an 80% surface coverage threshold. Our results show thatthe robots accurately localize all the failure sources and reach the coverage threshold required to complete the inspection. Thiswork demonstrates the viability of deploying robot swarms for inspection of potentially complex 3D environments.<br/

A Swarm Robotic Approach to Inspection of 2.5 D Surfaces in Orbit

Robotic inspection offers a robust, scalable, and flexible alternative to deploying fixed sensor networks or humaninspectors. While prior work has mostly focused on single robot inspections, this work studies the deployment of a swarm ofinspecting robots on a simplified surface of an in-orbit infrastructure. The robots look for points of mechanical failure and inspectthe surface by assessing propagating vibration signals. In particular, they measure the magnitude of acceleration they sense ateach location on the surface. Our choice for sensing and analyzing vibration signals is supported by the established position ofvibration analysis methods in industrial infrastructure health assessment. We perform simulation studies in Webots, a physicsbased robotic simulator, and present a distributed inspection algorithm based on bio-inspired particle swarm optimization andevolutionary algorithm niching techniques to collectively localize an a priori unknown number of mechanical failure points. Toperform the vibration analysis and obtain realistic acceleration data, we use the ANSYS multi-physics simulation software andmodel mechanical failure points as vibration sources on the surface. We deploy a robot swarm comprising eight robots of 10-cmsize that use a bio-inspired inchworming locomotion pattern. The swarm is deployed on 2.5D (that is curved 2D) cylindricalsurfaces with and without obstacles to investigate the robustness of the algorithm in environments with varying geometric complexity. We study three performance metrics: (1) proximity of the localized sources to their ground truth locations, (2) time tolocalize each source, and (3) time to finish the inspection task given an 80% surface coverage threshold. Our results show thatthe robots accurately localize all the failure sources and reach the coverage threshold required to complete the inspection. Thiswork demonstrates the viability of deploying robot swarms for inspection of potentially complex 3D environments.<br/

An Approach Based on Particle Swarm Optimization for Inspection of Spacecraft Hulls by a Swarm of Miniaturized Robots

The remoteness and hazards that are inherent to the operating environments of space infrastructures promote their need for automated robotic inspection. In particular, micrometeoroid and orbital debris impact and structural fatigue are common sources of damage to spacecraft hulls. Vibration sensing has been used to detect structural damage in spacecraft hulls as well as in structural health monitoring practices in industry by deploying static sensors. In this paper, we propose using a swarm of miniaturized vibration-sensing mobile robots realizing a network of mobile sensors. We present a distributed inspection algorithm based on the bio-inspired particle swarm optimization and evolutionary algorithm niching techniques to deliver the task of enumeration and localization of an a priori unknown number of vibration sources on a simplified 2.5D spacecraft surface. Our algorithm is deployed on a swarm of simulated cm-scale wheeled robots. These are guided in their inspection task by sensing vibrations arising from failure points on the surface which are detected by on-board accelerometers. We study three performance metrics: (1) proximity of the localized sources to the ground truth locations, (2) time to localize each source, and (3) time to finish the inspection task given a 75% inspection coverage threshold. We find that our swarm is able to successfully localize the present so

An Approach Based on Particle Swarm Optimization for Inspection of Spacecraft Hulls by a Swarm of Miniaturized Robots

The remoteness and hazards that are inherent to the operating environments of space infrastructures promote their need for automated robotic inspection. In particular, micrometeoroid and orbital debris impact and structural fatigue are common sources of damage to spacecraft hulls. Vibration sensing has been used to detect structural damage in spacecraft hulls as well as in structural health monitoring practices in industry by deploying static sensors. In this paper, we propose using a swarm of miniaturized vibration-sensing mobile robots realizing a network of mobile sensors. We present a distributed inspection algorithm based on the bio-inspired particle swarm optimization and evolutionary algorithm niching techniques to deliver the task of enumeration and localization of an a priori unknown number of vibration sources on a simplified 2.5D spacecraft surface. Our algorithm is deployed on a swarm of simulated cm-scale wheeled robots. These are guided in their inspection task by sensing vibrations arising from failure points on the surface which are detected by on-board accelerometers. We study three performance metrics: (1) proximity of the localized sources to the ground truth locations, (2) time to localize each source, and (3) time to finish the inspection task given a 75% inspection coverage threshold. We find that our swarm is able to successfully localize the present so