Papers for

field robotics engineers

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Trajectory comparison improved by curvature based time alignment

Comparing Trajectories from Positions Alone: Curvature-Based Time Alignment and Drift Error Metric

Abstract: In field robotics, acquiring independent large-scale reference trajectories more accurate than the evaluated estimates remains an open challenge. The domain is widely reliant on Absolute Trajectory Error (ATE) and Relative Pose Error (RPE), computed with automated tools, that rest on assumptions and evaluation parameters rarely made explicit. When unreported, the errors can be misleading and hinder fair comparisons. This paper introduces a trajectory-evaluation protocol for standardized and reliable accuracy assessment in state estimation, localization, and Simultaneous Localization And Mapping (SLAM). The approach combines a novel temporal alignment method based on curvature signals with an error metric normalized by travelled distance. We explicitly account for temporal synchronization, sampling alignment, and extrinsic calibration, quantifying their influence through a sensitivity analysis. The proposed protocol contributes to more rigorous, reproducible, and standardized trajectory evaluation.

Mon 14 SeptRobotics
The gist
Comparing robot movement paths accurately is hard because existing methods rely on some hidden assumptions and parameters that aren’t always clear. The authors introduce a new way to line up different robot paths in time using a shape-based feature called curvature, which helps make comparisons fairer and more reliable. They also propose a new error measurement that adjusts for how far the robot traveled. Their approach makes it easier to check how well robot navigation and mapping systems work by considering timing, sampling, and calibration differences.
Open → 2609.14936v1

Reconfigurable rover adapts shape for efficient obstacle climbing

GeoTrussRover: Morphological Computation with Contact-Semantic Control Primitives

Abstract: Reconfigurable robots can change their contact geometry when a fixed body cannot negotiate an obstacle. A variable-geometry truss (VGT) distributes this shape change through a load-bearing structure, but coupling it to a mobile base creates a high-dimensional coordination problem. GeoTrussRover combines an electrically actuated VGT, a wheeled base, and contact-semantic morphology planning and control. We solve one source traversal and extract four contact-semantic primitives that describe coordination among 21 members. Physics-constrained projection adapts them to unseen step heights with the same contact topology. When every phase remains feasible, adaptation does not recompute the complete motion. If one phase violates the new physical constraints, only that phase is recomputed. A full-space QP then tracks the adapted motion and corrects member and wheel errors. For transfer from 0.10m to 0.075m, the method reduces objective-function evaluations by 63.7% relative to full recomputation. Contact-phase feasibility analysis covers step heights from 0.10 to 0.46m, or 1.08 to 4.97 wheel radii, with the upper value near the theoretical feasible boundary. The electric prototype traverses 2.11 wheel radii. The resulting low-dimensional representation stores task coordination in a hyper-redundant, load-bearing morphology and reuses it during locomotion.

Thu 10 SeptRoboticsGraphicsNeural and Evolutionary Computing
The gist
Robots often struggle to climb over obstacles because their shapes can't easily change. The authors built a robot with a flexible truss structure on wheels, which lets it change shape to climb steps more easily. They found a way to break down its complex movements into simpler parts, so the robot can quickly adjust when facing new step heights without recalculating everything from scratch. Their robot prototype successfully climbed steps smaller than it was originally designed for, showing this method can save time and effort in controlling such complex robots.
Open → 2609.11361v1