Model predictive control based path following for a wheel-legged robot
- Resource Type
- Authors
- Ke Zhang; Yunpei Dang; Junzheng Wang; Hui Peng
- Source
- 2020 Chinese Control And Decision Conference (CCDC).
- Subject
- 050210 logistics & transportation
0209 industrial biotechnology
Robot kinematics
Computer science
05 social sciences
02 engineering and technology
Kinematics
Tracking (particle physics)
ComputingMethodologies_ARTIFICIALINTELLIGENCE
GeneralLiterature_MISCELLANEOUS
Mechanical system
Model predictive control
InformationSystems_MODELSANDPRINCIPLES
020901 industrial engineering & automation
Control theory
0502 economics and business
Robot
Legged robot
ComputingMethodologies_COMPUTERGRAPHICS
- Language
This paper proposes a model predictive control (MPC) based path following approach for tracking control of a wheel-legged robot named BIT-NAZA. The accuracy and stability of tracking control are still the main challenges for the autonomous wheel-legged robot due to its complex mechanical system. The wheel-legged robot has four legs and four wheels, and the wheels are installed on the end of the foot. To guarantee the tracking performance of the wheel-legged robot, effective approaches for reliable tracking control should be investigated with the consideration of the robot modeling, kinematics and dynamics constraints designing. In this paper, model predictive control based path following controller is designed and employed to improve the tracking performance for the wheel-legged robot BIT-NAZA. Experiments with the wheel-legged robot are performed to validate the performance of the proposed control strategy. The results demonstrate that the proposed methodology can achieve promising tracking performance in terms of accuracy.