Pith. sign in

REVIEW 3 cited by

Equivariant Systems Theory and Observer Design

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2006.08276 v3 pith:FR4SJ6QM submitted 2020-06-15 eess.SY cs.SY

classification eess.SYcs.SY
keywords systemsdesignequivariantstructurehomogeneouslie-groupspacesattitude
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

A wide range of system models in modern robotics and avionics applications admit natural symmetries. Such systems are termed equivariant and the structure provided by the symmetry is a powerful tool in the design of observers. Significant progress has been made in the last ten years in the design of filters and observers for attitude and pose estimation, tracking of homographies, and velocity aided attitude estimation, by exploiting their inherent Lie-group state-space structure. However, little work has been done for systems on homogeneous spaces, that is systems on manifolds on which a Lie-group acts rather than systems on the Lie-group itself. Recent research in robotic vision has discovered symmetries and equivariant structure on homogeneous spaces for a host of problems including the key problems of visual odometry and visual simultaneous localisation and mapping. These discoveries motivate a deeper look at the structure of equivariant systems on homogeneous spaces. This paper provides a comprehensive development of the foundation theory required to undertake observer and filter design for such systems.

Discussion (0). Sign in to comment.

Forward citations

Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. The Geometry of Extended Kalman Filters on Manifolds with Affine Connection

    eess.SY 2025-06 conditional novelty 7.0 of 10

    A geometric extended Kalman filter using affine connections, parallel transport, and curvature to transform Gaussian covariances between coordinates improves state estimation on manifolds.

  2. Leveraging Equivariances and Symmetries in the Control Barrier Function Synthesis

    eess.SY 2025-09 conditional novelty 6.0 of 10

    Symmetries in system dynamics and constraints let safety (barrier) functions be inferred across the whole state space from values on a small subset, and let partially known barrier functions seed new ones for asymmetr...

  3. Equivariant Filter for Relative Attitude and Target's Angular Velocity Estimation

    eess.SY 2025-06 conditional novelty 5.0 of 10

    A symmetry-based filter on SE(3) estimates relative attitude and target angular velocity from two vector measurements, with simulation and hardware validation.

Pith tools