| 1. |
- Duan, Anqing, et al.
(författare)
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Balancing Control of Wheeled-Legged Hexapedal Robots for Traversing Rough Terrains
- 2022
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Ingår i: 2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1905-1910
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Konferensbidrag (refereegranskat)abstract
- Robots with wheeled-legged morphology usually inherit the merits from both wheeled vehicles and legged machines. The hybrid structure can greatly enhance the mo-bility capabilities of locomotive robots, making these robots adaptable to a wide range of working conditions. In this paper, we specifically consider the balancing control problem of a wheeled-legged hexapedal robot. The employed robot platform has six actively articulated wheels that can be independently controlled. More precisely, each wheel of the robot is attached to a hub using the three-bar linkage mechanism, where one of the links is realized in the form of an electric linear actuator that can extend or retract to drop or lift the corresponding wheel following an arc curve, respectively. Our goal is to devise a control strategy to simultaneously command all six linear actuators such that the robot can keep stable when traversing rough terrains. To this end, we equip the robot with an IMU sensor to monitor the status of the chassis during driving the robot. By analytically establishing the kinematic relationship between the motion of the rod of the linear actuators and the angle change of the chassis, we can make the robot maintain horizontal by means of active suspension given the current tilt angle. The effectiveness of the proposed strategy is verified with both simulation and preliminary real experiments.
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| 2. |
- Li, Yuchao, et al.
(författare)
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A Geometric Programming Approach to the Optimization of Mechatronic Systems in Early Design Stages
- 2016
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Ingår i: 2016 IEEE INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT MECHATRONICS (AIM). - : IEEE conference proceedings. - 9781509020652 ; , s. 1351-1356
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Konferensbidrag (refereegranskat)abstract
- This paper evaluates geometric programming as a solver to optimize mechatronic system design in a holistic manner to aid early design decisions. Mechatronic systems design optimization requires complex and often non-convex functions as design objectives and constraints. Currently the solutions are primarily based on randomized search methods, e.g., genetic algorithms, and they are time-consuming. This paper converts complex constraints and objectives into approximate posynomial forms, which can then be used with disciplined convex optimization to significantly reduce the computation time for optimization. The approach is compared to the previous research using a mechatronic servo system design case study consisting of a motor, a shaft, two planetary gears and a rotational load. The result confirms that the geometric programming approach improves both computation speed and accuracy.
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