Minimum control effort trajectory planning and tracking of the CEDRA brachiation robot

Author:

Meghdari Ali,Lavasani Seyyed Mohammad H.,Norouzi Mohsen,Mousavi Mir Saman Rahimi

Abstract

SUMMARYThe control of a brachiation robot has been the primary objective of this study. A brachiating robot is a type of a mobile arm that is capable of moving from branch to branch similar to a long-armed ape. In this paper, to minimize the actuator work, Pontryagin's minimum principle was used to obtain the optimal trajectories for two different problems. The first problem considers “brachiation between fixed branches with different distance and height,” whereas the second problem deals with the “brachiating and catching of a moving target branch”. Theoretical results show that the control effort in the proposed method is reduced by 25% in comparison with the “target dynamics” method which was proposed by Nakanishi et al. (1998)16 for the same type of robot. As a result, the obtained optimal trajectory also minimizes the brachiation time. Two kinds of controllers, namely the proportional-derivative (PD) and the adaptive robust (AR), were investigated for tracking the proposed trajectories. Then, the previous method on a set-point controller for acrobat robots is improved to represent a new AR controller which allows the system to track the desired trajectory. This new controller has the capability to be used in systems which have uncertainties in the kinematic and dynamic parameters. Finally, theoretical results are presented and validated with experimental observations with a PD controller due to the no chattering phenomenon and small computational efforts.

Publisher

Cambridge University Press (CUP)

Subject

Computer Science Applications,General Mathematics,Software,Control and Systems Engineering

Cited by 16 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Ricmonk: A Three-Link Brachiation Robot with Passive Grippers for Energy-Efficient Brachiation;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

2. Trajectory Generation and Tracking Based on Energy Minimization for a Four-Link Brachiation Robot;2023 IEEE International Conference on Unmanned Systems (ICUS);2023-10-13

3. A Deep Reinforcement Learning Control Method for a Four-Link Brachiation Robot;2023 2nd International Conference on Machine Learning, Cloud Computing and Intelligent Mining (MLCCIM);2023-07-25

4. AcroMonk: A Minimalist Underactuated Brachiating Robot;IEEE Robotics and Automation Letters;2023-06

5. Brachiation Robot Dynamics Modelling;2022 10th RSI International Conference on Robotics and Mechatronics (ICRoM);2022-11-15

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