Development of a Portable Hybrid Pendubot-Acrobot Robotic Platform for On and Off-Campus Teaching and Learning

Ng, Raymond W. M.; Tang, Yunxi; Lin, Hongbin; Chu, Xiangyu; Au, Kwok Wai Samuel

doi:10.23919/acc50511.2021.9482939

Cited by 2 publications

(1 citation statement)

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“…Due to mechanical design and control complexity, all reported platforms in the literature were constructed for a single purpose, either a pendubot or an acrobot. Only a recent parallel development showed a system that could potentially be used as a testbed for both the pendubot and acrobot [14]. The system is provided with open source MATLAB code.…”

Section: Related Workmentioning

confidence: 99%

Open Source Dual-Purpose Acrobot and Pendubot Platform: Benchmarking Control Algorithms for Underactuated Robotics

Wiebe,

Kumar,

Shala

et al. 2024

IEEE Robot. Automat. Mag.

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Recent interest in the control of underactuated robots has surged significantly due to the impressive athletic behaviors shown by robots developed by, e.g., Boston Dynamics (https:// www.bostondynamics.com), Agility Robotics (https://agility robotics.com/robots), and the Massachusetts Institute of Technology [1]. This gives rise to the need for canonical robotic hardware setups for studying underactuation and comparing learning and control algorithms for their performance and robustness. Similar to OpenAIGym [2] and Stable Baselines [3], which provide simulated benchmarking environments and baselines for reinforcement learning algorithms, there is a need for benchmarking learning and control methods on real canonical hardware setups. To encourage reproducibility in robotics and artificial intelligence research, these hardware setups should be affordable and easy to manufacture with offthe-shelf components, and the accompanying software should be open source. Acrobots and pendubots are classical textbook examples of canonical underactuated systems with strong nonlinear dynamics, and their swing-up and upright balancing is considered a challenging control problem, especially on real hardware.

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Section: Related Workmentioning

confidence: 99%