Here are indications that falling for a robot is possible
[PDF File]Temporal Sequence Learning, Prediction, and Control - A ...
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Leaning sideways will lead to a reflex-like antagonistic motor action in order to prevent falling. 4) The motor action of feeding will lead to a taste sensation. 5) The bell precedes the food in Pavlov’s classical conditioning experiments. 6) The position of a robot arm is preceded by the force patterns which converge onto it.
[PDF File]The Anatomy of a Fall: Automated Real-time Analysis of Raw ...
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the fall, which indicate robot instability. (b) The robot falls backward, caused by smaller response velocity of the pelvis than the reference one. It can be predicted by the changed pressure distribution on the foot sole and the later-than-expected heel strike events. Fig. 1: Two examples of falling of a bipedal walking robot.
[PDF File]Evolutionary discovery of self-stabilized dynamic gaits for a ...
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Fig. 1. Robot components (a) and different qualitative behaviors observed in tank experiments as the mean robot density of the robot was varied, by changing the inflation state of the floating module: crawling (b), running (c) and sculling (d). III. SAGITTAL MODEL In order to explore the design space of our robot, in the fol-
[PDF File]Modelling and Analyzing Adaptive Self-Assembly Strategies ...
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Such features make the self-assembly robot swarm a challenging scenario to engineer. In [16], di erent self-assembly strategies are proposed to carry out tasks that range from hill-crossing and hole-crossing to robot rescue: case by case, depending e.g. on the steep of the hill, the width of the hole, the location of the robot to be
[PDF File]ChARMin: A Robot for Pediatric Arm Rehabilitation
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The robot should be strong enough to guide a paralyzed arm and counteract a spastic arm and, therefore, prevent a possible collision with the patient’s body. Furthermore, the robot should resist even a relatively strong patient when using the robot as an assessment tool to determine isometric force.
[PDF File]Learning Acceptable Windows of Contingency
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produce reliable indications of whether the events were self-generated, socially contingent, or neither. We describe our results below. II. THE TIME WINDOW MODEL Before describing the physical robot, we will first de-scribe our general method for learning contingency time windows. Assume that the robot is attempting to learn via a noisy
[PDF File]Protograms - Stanford University
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the robot is influenced by two imaginary forces- one attracting it to the goal, another repelling it from nearby obstacles. The movement of the robot is dictated by the sum of these two imaginary forces. This procedure has been implemented widely in conventional languages, but it is possible to view it as an interaction between two protograms. The
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