The sensing and communication capabilities of Wireless Sensor Networks (WSNs) promote the development of various emerging service applications based on target positioning. Considering that the power inspection robot usually operates in complex environments

small spaces

and dense equipment

this paper researches the intelligent positioning algorithm and experimental evaluations of distributed WSNs for inspection robots

aiming to solve the problem of large positioning errors in wireless communication and measurement processes. Firstly

a wireless mapping model between wireless base stations and wireless beacons is established with use of noisy time difference of arrival. Secondly

a complete nonlinear analytical model that can characterize the distributed location of inspection robots is derived considering the wireless ranging errors. Then

the fitness function

inertia weight factor

and mutation operation of particle swarm optimization are designed with distributed location as the initial search value. Finally

simulation and experimental evaluations of inspection robot wireless positioning are conducted in terms of ranging noise and positioning accuracy. The experimental results indicate that the proposed distributed joint particle swarm optimization positioning algorithm for inspection robot has higher positioning accuracy compared to other algorithms

and can provide technical support for applications including collaborative automation of power equipment clusters.