Multibody Simulation of the Path Tracking Performance of a Hybrid Leg-wheel Ground Mobile Robot

2016 ◽  
Author(s):  
Luca Bruzzone ◽  
Pietro Fanghella ◽  
Matteo Nisi ◽  
Giuseppe Quaglia
Keyword(s):  
Mobile Robot ◽  
Path Tracking ◽  
Tracking Performance ◽  
Multibody Simulation

scholarly journals Functional Design of a Hybrid Leg-Wheel-Track Ground Mobile Robot

Machines ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 10
Author(s):  
Luca Bruzzone ◽  
Mario Baggetta ◽  
Shahab E. Nodehi ◽  
Pietro Bilancia ◽  
Pietro Fanghella
Keyword(s):  
Mobile Robot ◽  
High Energy ◽  
General Purpose ◽  
Stair Climbing ◽  
Functional Design ◽  
Multibody Simulation ◽  
Embodiment Design ◽  
Locomotion System ◽  
Hybrid Locomotion ◽  
Wheel Track

This paper presents the conceptual and functional design of a novel hybrid leg-wheel-track ground mobile robot for surveillance and inspection, named WheTLHLoc (Wheel-Track-Leg Hybrid Locomotion). The aim of the work is the development of a general-purpose platform capable of combining tracked locomotion on irregular and yielding terrains, wheeled locomotion with high energy efficiency on flat and compact grounds, and stair climbing/descent ability. The architecture of the hybrid locomotion system is firstly outlined, then the validation of its stair climbing maneuver capabilities by means of multibody simulation is presented. The embodiment design and the internal mechanical layout are then discussed.

Robust PID Tuning. Application to a Mobile Robot Path Tracking Problem

2000 ◽  
Vol 33 (4) ◽  
pp. 559-564
Author(s):  
Julio E. Normey-Rico ◽  
Ismael Alcalá ◽  
Juan Gómez-Ortega ◽  
Eduardo F. Camacho
Keyword(s):  
Mobile Robot ◽  
Path Tracking ◽  
Tracking Problem ◽  
Pid Tuning ◽  
Robot Path

Tracking Control of a Nonholonomic Mobile Robot Using Neural Network

2015 ◽  
pp. 631-661 ◽  
Author(s):  
Şahin Yildirim ◽  
Sertaç Savaş
Keyword(s):  
Neural Networks ◽  
Mobile Robot ◽  
Tracking Error ◽  
Back Propagation ◽  
Open Loop ◽  
Tracking Performance ◽  
Back Propagation Algorithm ◽  
Tracking Errors ◽  
Nonholonomic Mobile Robot ◽  
Feed Forward Neural Networks

The goal of this chapter is to enable a nonholonomic mobile robot to track a specified trajectory with minimum tracking error. Towards that end, an adaptive P controller is designed whose gain parameters are tuned by using two feed-forward neural networks. Back-propagation algorithm is chosen for online learning process and posture-tracking errors are considered as error values for adjusting weights of neural networks. The tracking performance of the controller is illustrated for different trajectories with computer simulation using Matlab/Simulink. In addition, open-loop response of an experimental mobile robot is investigated for these different trajectories. Finally, the performance of the proposed controller is compared to a standard PID controller. The simulation results show that “adaptive P controller using neural networks” has superior tracking performance at adapting large disturbances for the mobile robot.

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