In this study, we concisely investigate two phases in the hybrid A-star algorithm for non-holonomic robots: the forward search phase and analytic expansion phase. The forward search phase considers the kinematics of the robot model in order to plan continuous motion of the robot in discrete grid maps. Reeds-Shepp (RS) curve in the analytic expansion phase augments the accuracy and the speed of the algorithm. However, RS curves are often produced close to obstacles, especially at corners. Consequently, the robot may collide with obstacles through the process of movement at these corners because of the measurement errors or errors of motor controllers. Therefore, we propose an improved RS method to eventually improve the hybrid A-star algorithm’s performance in terms of safety for robots to move in indoor environments. The advantage of the proposed method is that the non-holonomic robot has multiple options of curvature or turning radius to move safer on pathways. To select a safer route among multiple routes to a goal configuration, we introduce a cost function to evaluate the cost of risk of robot collision, and the cost of movement of the robot along the route. In addition, generated paths by the forward search phase always consist of unnecessary turning points. To overcome this issue, we present a fine-tuning of motion primitive in the forward search phase to make the route smoother without using complex path smoothing techniques. In the end, the effectiveness of the improved method is verified via its performance in simulations using benchmark maps where cost of risk of collision and number of turning points are reduced by up to around 20%.
This study aims to interpret and apply Asimov's Three Laws of Robotics to home service robots. An agent is developed herein with the ability to focus its attention on human beings' health, particularly the elderly and the diseased, by delivering food. The agent is developed on a cognitive agent architecture, state, operator, and result (Soar), to enable effective reasoning and decision-making skills. This study deals with basic home care services, such as food delivery and emergency response; therefore, common food care and emergency rules are newly proposed based on the priority values that correspond to a family's circumstances and/or emergency levels. Asimov's Three Laws are modified to aid the home service robot to follow a predetermined order in selecting a food item or recommending an alternative food item suitable for its user's prevailing health condition. Experimental results confirm that reasoning and decision-making of the proposed agent are logically and ethically valid for a home service robot and ensure compliance with both the original and modified Asimov's Three Laws.
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