Autonomous robotic exploration of unknown soft objects
Year: 2026
Type: article
Abstract: Robotic exploration of unknown soft objects presents significant challenges for autonomous systems due to unpredictable deformations and shape changes during manipulation. To address this, we propose a framework that integrates topology-aware 3D reconstruction with a topology-guided motion planner, enabling the discovery and reconstruction of previously hidden or concave regions. This topology-aware 3D reconstruction employs a novel representation of deformable objects by combining Cylinder Čech Complexes with point clouds, enabling rapid tracking of significant topology changes and detection of non-manifold boundaries. The topology analysis and canonical reconstruction guide motion planning by optimising grasp points and planning trajectories to reveal previously unseen surfaces through two actions: turning over and stretching. We validated our algorithm through simulations and experiments using the da Vinci Research Kit, demonstrating successful exploration with two or three manipulators. We showed it can fully explore surfaces of two everyday objects, a beanie and a rubber glove, and two cadaveric organs, a liver and a colon, within seven manipulations. Our method achieved a 45.6% improvement in 3D reconstruction accuracy compared to state-of-the-art point-cloud-based methods while also demonstrating the capability to detect and fix non-manifold geometry.
Institutions: University of Leeds, University of Technology Sydney
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,400
OpenAlex ID: W7129190584