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Arm. The lateral error has been measured with an external distance
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Mixed effects models to assess in the event the unique variables analyzed (difference of speeds, speed of the player and speed of the opponent) can discriminate among the type of interaction, finding that only the collective variable in the relative speeds can discriminate the two kinds of programmed agents from genuine human interaction (Section 4.3).three. Components AND METHODS3.1. EXPERIMENTAL PROCEDUREIn this experiment, human participants were allocated computers to interact in pairs, inside a shared perceptual space, where some opponents had been other human participants and some opponents had been computerized agents (bots) but participants were unaware on the nature of their opponents. Our intention was not to make a duplication of Auvray's experiment where each participant simultaneously encounters a human partner, a mobile agent and a static a single. In our case, every participant received only a single stimulus in one of many following scenarios: human vs. human, human vs. "oscillatory agent" and human vs. "shadow agent." The "oscillatory agent" was programmed to deploy a sinusoidal behavior (describing a sinusoidal trajectory of 0.five Hz and 200 pixels of amplitude), predictable and deterministic. In contrast, the "shadow agent" was in a position to show an irregular pattern since it consists of a "shadow image" of the participant (i.e., a bot that generates a movement strictly identical towards the participant trajectory but delayed 400 ms. in time and 125 pixels in space). Participants had been instructed to make an effort to detect wether their opponent was human or not and asked to fill a questionary (despite the fact that the analysis of the participants responses is out on the scope of this paper). When participants arrived in the laboratory they were randomly assigned to a workstation and had been offered with headphones. They have been informed that the study involved two components, every independent from the other and that the first one--training stage--would take approximately 3 min and the second one-- evaluation stage--a further 10 min. In an effort to guarantee confidentiality during the study, identification codes/nicknames had been chosen by the participants. Throughout the experiment, participants were supplied with verbal instructions with regards to the structure with the experiment and their sections. Within the training stage, the participants had been informed that it was a straightforward "proof of concept" stage and that the purpose was only to find out how the platform worked. Participants had been totally free to move the mouse as they pleased throughout three sessions of 1 min each having a quick break involving them. They played consecutively against 3 bots of rising difficulty within the interaction: a static bot, a bot moving at a continual low speed along with a bot moving at a continuous medium speed. Following that, they were informed of the aim and guidelines in the evaluation a part of the experiment. The experiment consisted of ten sessions of 40 s every single. In every single session: (i) every single participant was randomly assigned an opponent (human-human or human-bot) to explore the virtual space; (ii) participants had been asked to move their mouses as a way to detect the movement of their assigned opponents, (iii) immediately after every single session, participants were asked tomake a option between the two selections displayed around the screen in an effort to guess no matter if their opponent was a human or a bot, and (iv), finally, participants were informed around the screen no matter whether or not they had guessed effectively. Soon after the ten sessions had been completed, the experiment was declared finish.
Arm. The lateral error has been measured with an external distance measure laser so as to have true values concerning the distance among the car plus the docking point.Sensors 2013, 13 Figure ten. Validation tests: input variables and action lateral controller.Table two. Departure and arrival points in unique situations. It's important so as to have greater docking within the charging station. Lastly, an experiment from a higher distance, both in X and Y axes (7.5 and 1.25 m, respectively), has been performed. Figure 11 shows the position in Cartesian coordinates in the perception technique, filtered and translated towards the front manage point. As inside the earlier experiments, the car reaches the docking point with an error reduce than five cm. Figure 11. Positions offered from the perception system inside the final experiment.Figure 12. Lateral command and variables in the handle inside the final experiment.Figure 12 shows the evolution with the steering position and each input variables. The manage action is soft and continuous, along with the car in no way overpasses the reference line (zero inside the Y axis). Around 20 s from the experiment, the automobile arrived to the center of your docking line, but it is just not absolutely straight;Sensors 2013,then the angular action turned the steering wheel till (35 s) the car reaches the docking point having a lateral and angular error of two cm and 0.four degrees, respectively. Then, the automatic charging arm is ready to charge the batteries. five. Conclusions and Future Work In this work, a manage architecture for autonomous docking systems, primarily based on an embedded perception program in an autonomous electric vehicle along with a recharging station for urban parking locations, is presented. Our strategy has been developed under the framework from the AMARE project, applying the information supplied by an infrared camera and diodes installed within the recharging station. The details from this sensor had been processed and filtered then sent for the handle stage for automatic docking of your automobile. The proposed architecture is quickly adaptable to any industrial electric automobile. Various experiments, departing from unique points, show very good behavior with the proposed technique. Each lateral and longitudinal errors are decrease than the limits from the charging station. The proposed controller is simple and intuitive for tuning, as well as the gains can be adapted according to the unique vehicles' characteristics. The technique presented within this paper is really operating within a genuine situation inside the city of Paris (http://www.modulowatt.com/Modulowatt_video_Mobilier_Urbain_Intelligent_fr.html) as a permanent demonstrator on the AMARE project. The proposed operate relies solely around the facts from the camera on board the automobile. When the charging station is out-of-range, the camera is obstructed, the signal is also noisy or is lost (e.g., in the event the steering wheel turns a lot), the autonomous docking maneuver is stopped until the signal is perceived once more. Because of this, other sensors and data data could be added for the handle architecture proposed, such as CAN frame data or odometer data, so as to raise the redundancy along with the robustness from the program in future operate. Furthermore, actions more than the gear shift might be deemed for more constrained scenarios.
 
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Mixed effects models to assess in the event the unique variables analyzed (difference of speeds, speed of the player and speed of the opponent) can discriminate among the type of interaction, finding that only the collective variable in the relative speeds can discriminate the two kinds of programmed agents from genuine human interaction (Section 4.3).three. Components AND METHODS3.1. EXPERIMENTAL PROCEDUREIn this experiment, human participants were allocated computers to interact in pairs, inside a shared perceptual space, where some opponents had been other human participants and some opponents had been computerized agents (bots) but participants were unaware on the nature of their opponents. Our intention was not to make a duplication of Auvray's experiment where each participant simultaneously encounters a human partner, a mobile agent and a static a single. In our case, every participant received only a single stimulus in one of many following scenarios: human vs. human, human vs. "oscillatory agent" and human vs. "shadow agent." The "oscillatory agent" was programmed to deploy a sinusoidal behavior (describing a sinusoidal trajectory of 0.five Hz and 200 pixels of amplitude), predictable and deterministic. In contrast, the "shadow agent" was in a position to show an irregular pattern since it consists of a "shadow image" of the participant (i.e., a bot that generates a movement strictly identical towards the participant trajectory but delayed 400 ms. in time and 125 pixels in space). Participants had been instructed to make an effort to detect wether their opponent was human or not and asked to fill a questionary (despite the fact that the analysis of the participants responses is out on the scope of this paper). When participants arrived in the laboratory they were randomly assigned to a workstation and had been offered with headphones. They have been informed that the study involved two components, every independent from the other and that the first one--training stage--would take approximately 3 min and the second one-- evaluation stage--a further 10 min. In an effort to guarantee confidentiality during the study, identification codes/nicknames had been chosen by the participants. Throughout the experiment, participants were supplied with verbal instructions with regards to the structure with the experiment and their sections. Within the training stage, the participants had been informed that it was a straightforward "proof of concept" stage and that the purpose was only to find out how the platform worked. Participants had been totally free to move the mouse as they pleased throughout three sessions of 1 min each having a quick break involving them. They played consecutively against 3 bots of rising difficulty within the interaction: a static bot, a bot moving at a continual low speed along with a bot moving at a continuous medium speed. Following that, they were informed of the aim and guidelines in the evaluation a part of the experiment. The experiment consisted of ten sessions of 40 s every single. In every single session: (i) every single participant was randomly assigned an opponent (human-human or human-bot) to explore the virtual space; (ii) participants had been asked to move their mouses as a way to detect the movement of their assigned opponents, (iii) immediately after every single session, participants were asked tomake a option between the two selections displayed around the screen in an effort to guess no matter if their opponent was a human or a bot, and (iv), finally, participants were informed around the screen no matter whether or not they had guessed effectively. Soon after the ten sessions had been completed, the experiment was declared finish.