IMU-based pose-estimation for spherical robots with limited resources

Jasper Zevering*, A. Bredenbeck, Fabian Arzberger, Dorit Borrmann, Andreas Nüchter

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review


Spherical robots are a robot format that is not yet thoroughly studied for the application of mobile mapping. However, in contrast to other forms, they provide some unique advantages. For one, the spherical shell provides protection against harsh environments, e.g., guarding the sensors and actuators against dust and solid rock. This is particularly useful in space applications. Furthermore, the inherent rotation the robot uses for locomotion can be exploited to measure in all directions without having the sensor itself actuated. A reasonable estimation of the robot pose is required to exploit this rotation in combination with sensor data to create a consistent environment map. This raises the need for interpolating instances for calculation-intensive slow algorithms such as optical localization algorithms or as an initial estimate for subsequent simultaneous localization and mapping (SLAM). In such cases, inertial measurements from sensors such as accelerometers and gyroscopes generate a pose estimate for these interpolation steps. The paper presents a pose estimation procedure based on inertial measurements, that exploits the known dynamics of a spherical robot. It emphasizes a low jitter to maintain constant world measurements during standstill and avoids exponentially growing error in position estimates. Evaluating the position and orientation estimates with given ground truth frames shows that we reduce the jitter in orientation and handle slip and partly slide behavior better than other commonly used filters such as the Madgwick filter.
Original languageEnglish
Title of host publication2021 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)
Publication statusPublished - 2021
Externally publishedYes


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