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Publications (2)2.56 Total impact

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    ABSTRACT: In this paper, we propose a new wheeled mobile robot (WMR) with a passive linkage-type locomotive mechanism that allows the WMR to adapt passively to rough terrain and climb up stairs, making it ideal for applications such as building inspection, building security, and military reconnaissance. A simple four-bar linkage mechanism and a limited pin joint are proposed after considering two design needs: adaptability and passivity. To improve the WMR’s ability to climb stairs, we divided the stair-climbing motion into several stages, taking into consideration the status of the points of contact between the driving wheels and the step. For each of the suggested stages, a kinetic analysis was accomplished and validated using the multi-body dynamic analysis software package ADAMS. The object functions are presented for the stages that influence the WMR’s ability to climb stairs. The optimization of the object functions is carried out using the multi-objective optimization method.
    Journal of Intelligent and Robotic Systems 07/2007; 49:325-354. · 0.81 Impact Factor
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    ABSTRACT: Mobile robots are being developed for building inspection and security, military reconnaissance, and planetary exploration. In such applications, the robot is expected to encounter rough terrain. In rough terrain, it is important for mobile robots to maintain adequate traction as excessive wheel slip causes the robot to lose mobility or even be trapped. This paper proposes a traction control algorithm that can be independently implemented to each wheel without requiring extra sensors and devices compared with standard velocity control methods. The algorithm estimates the stick-slip of the wheels based on estimation of angular acceleration. Thus, the traction force induced by torque of wheel converses between the maximum static friction and kinetic friction. Simulations and experiments are performed to validate the algorithm. The proposed traction control algorithm yielded a 40.5% reduction of total slip distance and 25.6% reduction of power consumption compared with the standard velocity control method. Furthermore, the algorithm does not require a complex wheel-soil interaction model or optimization of robot kinematics.
    Autonomous Robots 01/2007; 23(1):3-18. · 1.75 Impact Factor