The E-Rocket: Low-cost Testbed for TVC Rocket GNC Validation
Pith reviewed 2026-05-22 12:47 UTC · model grok-4.3
The pith
The E-Rocket provides a low-cost electric platform to validate thrust vector control for rocket guidance, navigation and control.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
The E-Rocket demonstrates that a low-cost assembly of commercial parts, 3D-printed components, and a servo-actuated gimbal with contra-rotating DC brushless motors, paired with PX4 and ROS 2 avionics, can achieve accurate trajectory tracking in indoor motion-capture tests using a baseline PID controller, thereby establishing its suitability as a versatile testbed for rocket GNC algorithms based on thrust vector control.
What carries the argument
The servo-actuated gimbal mechanism with contra-rotating DC brushless motors that supplies thrust vector control to the small electric rocket.
Load-bearing premise
Indoor motion-capture validation with a baseline PID controller on a small electric prototype will translate to useful insights for real rocket GNC under outdoor flight conditions with different dynamics and disturbances.
What would settle it
Outdoor flight tests that measure large drops in trajectory accuracy from wind or scaling effects not observed indoors would falsify the claim that indoor results reliably inform broader rocket GNC validation.
Figures
read the original abstract
This paper presents the E-Rocket, an electric-powered, low-cost rocket prototype for validation of Guidance, Navigation & Control (GNC) algorithms based on Thrust Vector Control (TVC). Relying on commercially available components and 3D printed parts, a pair of contra-rotating DC brushless motors is assembled on a servo-actuated gimbal mechanism that provides thrust vectoring capability. A custom avionics hardware and software stack is developed considering a dual computer setup which leverages the capabilities of the PX4 autopilot and the modularity of ROS 2 to accommodate for tailored GNC algorithms. The platform is validated in an indoor motion-capture arena using a baseline PID-based trajectory tracking controller. Results demonstrate accurate trajectory tracking and confirm the suitability of the E-Rocket as a versatile testbed for rocket GNC algorithms.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper presents the E-Rocket, a low-cost electric-powered rocket prototype for validating TVC-based GNC algorithms. It uses commercially available components and 3D-printed parts with contra-rotating DC brushless motors on a servo-actuated gimbal for thrust vectoring, a dual-computer avionics stack integrating PX4 autopilot and ROS 2, and indoor motion-capture validation with a baseline PID trajectory-tracking controller. Results show accurate tracking and support the platform's suitability as a versatile testbed.
Significance. If the results hold, the E-Rocket supplies an accessible, reproducible hardware platform using off-the-shelf parts and open-source software for indoor GNC testing. This lowers barriers for algorithm development and provides physical motion-capture benchmarks against which controllers can be evaluated, a concrete strength for experimental systems work.
major comments (1)
- Validation/Results: The claim of 'accurate trajectory tracking' and suitability for GNC algorithms rests on qualitative demonstration; no quantitative metrics (e.g., RMS position error, peak deviation, or attitude RMSE) or data tables are referenced, weakening the evidential basis for the central inference.
minor comments (2)
- Abstract: Specify the commanded trajectory (e.g., hover, straight-line, or figure-eight) and arena size to give readers immediate context for the reported tracking performance.
- Hardware/Avionics sections: Clarify gimbal servo bandwidth, motor thrust-to-weight ratio, and exact PX4-ROS 2 message interfaces to aid reproducibility by other groups.
Simulated Author's Rebuttal
We thank the referee for the constructive comment on the validation and results section. We address the point below.
read point-by-point responses
-
Referee: Validation/Results: The claim of 'accurate trajectory tracking' and suitability for GNC algorithms rests on qualitative demonstration; no quantitative metrics (e.g., RMS position error, peak deviation, or attitude RMSE) or data tables are referenced, weakening the evidential basis for the central inference.
Authors: We agree that the manuscript would benefit from quantitative support for the tracking performance claims. The indoor motion-capture experiments recorded position and attitude data that can be used to compute RMS position error, peak deviation, and attitude RMSE. In the revised version we will add these metrics, computed over multiple trials, together with a summary table. This will strengthen the evidential basis for the suitability of the E-Rocket as a GNC testbed while preserving the existing qualitative figures. revision: yes
Circularity Check
No circularity: experimental validation against external motion-capture benchmarks
full rationale
The paper presents a hardware prototype and reports results from physical indoor tests using a motion-capture system and baseline PID controller. No mathematical derivation chain, fitted parameters, or predictions are claimed; the central claim of suitability rests directly on measured trajectory tracking performance against an independent external reference. This is self-contained experimental work with no reduction of outputs to inputs by construction or self-citation.
Axiom & Free-Parameter Ledger
Reference graph
Works this paper leans on
-
[1]
Hauser, J., Sastry, S., and Meyer, G. (1992). Nonlinear control design for slightly non-minimum phase systems: Application to V/STOL aircraft.Automatica, 28(4), 665–679
work page 1992
-
[2]
Hua, M.D., Hamel, T., Morin, P., and Samson, C. (2013). Introduction to feedback control of underac- tuated VTOL vehicles: A review of basic control design ideas and principles.IEEE Control Systems Magazine, 33(1), 61–75
work page 2013
-
[3]
Scherer, S., and Pascoal, A. (2024). Pegasus simulator: An Isaac Sim Framework for Multiple Aerial Vehicles Simulation. In2024 International Conference on Un- manned Aircraft Systems (ICUAS)
work page 2024
-
[4]
Linsen, R. et al. (2022). Optimal Thrust Vector Control of an Electric Small-Scale Rocket Prototype. In2022 International Conference on Robotics and Automation (ICRA). Philadelphia, PA, USA
work page 2022
-
[5]
Woodall, W. (2022). Robot operating system 2: Design, architecture, and uses in the wild.Science Robotics, 7(66)
work page 2022
-
[6]
Meier, L., Honegger, D., and Pollefeys, M. (2015). PX4: A node-based multithreaded open source robotics frame- work for deeply embedded platforms. In2015 IEEE international conference on robotics and automation (ICRA)
work page 2015
-
[7]
Pardo-Castellote, G. (2003). OMG data-distribution ser- vice: architectural overview. In23rd International Con- ference on Distributed Computing Systems Workshops
work page 2003
-
[8]
Ragab, M. and Cheatwood, F.M. (2015). Launch Vehicle Recovery and Reuse. InAIAA SPACE 2015 Conference and Exposition. Pasadena, California
work page 2015
-
[9]
Santos, P. and Oliveira, P. (2025). Pitch Plane Trajectory Tracking Control for Sounding Rockets via Adaptive Feedback Linearization. In2025 IEEE Aerospace Con- ference. Big Sky, Montana, USA
work page 2025
-
[10]
Spannagl, L. et al. (2021). Design, Optimal Guidance and Control of a Low-cost Re-usable Electric Model Rocket. In2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Prague, Czech Republic
work page 2021
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.