Answers are grounded in this paper and cite their sources.
This paper reports the joint outdoor characterisation of detection, mapping, local re-planning and grasping running concurrently on one 4 GB embedded graphics processing unit module aboard a 12.982 kg six-wheel rocker-bogie rover, and the power it draws. Platforms of this class are characterised one subsystem at a time. The high-level stack runs as Robot Operating System 2 (ROS 2) nodes. On a held-out split of 250 annotated outdoor frames spanning overcast and direct sunlight, a half-precision single shot multibox detector on a MobileNetV2 backbone reached 89.4% mean average precision at 0.5 intersection over union while the vehicle sustained 14.5 frames per second with mapping, planning and telemetry resident. Planar light detection and ranging inertial mapping over a bounded 10 m by 10 m grass plot returned 11.2 cm positional root mean square error, with 220 ms local re-planning latency, bounding safe ground speed near 0.34 m s −1. Thirty autonomous pick-and-place trials on a 12 cm cylindrical target succeeded 23 times: 76.7%, Wilson 95% interval 0.59–0.88. Mean terminal draw under mixed duty was 38.5 W, exceeding the duty-weighted prediction from three isolated states by 16.3 W and giving about 5.3 h of derived endurance. Perception , mapping, manipulation and terminal power were measured together on one sub-13 kg field platform, and the shortfall shows that a budget built from isolated subsystem states underestimates what this autonomy actually draws.
No takes yet. Share an insight, caveat, or question.
Sahay et al. (2026) studied this question.
Synapse has enriched 8 closely related papers on similar clinical questions. Consider them for comparative context: