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Abstract: With the accelerated development of robot technologies, optimal control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of the history of sensor values, guided by the goals, intentions, objectives, learning schemes, and so forth. While very successful with classical robots, these methods run into severe difficulties when applied to soft robots, a new field of robotics with large interest for human-robot interaction. We claim that a novel controller paradigm opens new perspective for this field. This paper applies a recently developed neuro controller with differential extrinsic synaptic plasticity to a muscle-tendon driven arm-shoulder system from the Myo-robotics toolkit. In the experiments, we observe a vast variety of self-organized behavior patterns: when left alone, the arm realizes pseudo-random sequences of different poses. By applying physical forces, the system can be entrained into definite motion patterns like wiping a table. Most interestingly, after attaching an object, the controller gets in a functional resonance with the object’s internal dynamics, starting to shake spontaneously bottles half-filled with water or sensitively driving an attached pendulum into a circular mode. When attached to the crank of a wheel the neural system independently discovers how to rotate it. In this way, the robot discovers affordances of objects its body is interacting with. We also discuss perspectives for using this controller paradigm for intention driven behavior generation.
| Overview | Compiled clip of all experiments | Video 1 |
| Handshake | Human robot interaction by manually imposing a periodic movement | Video 2 |
| Bottle swing | Excitation of a circular pendulum mode | Video 3 |
| Bottle swing measure | Motors are stopped. Recording spring forces of swinging suspended bottle | Video 4 |
| Shaking vertically | A half filled bottle is vertically attached to the tip of the arm: shaking of the bottle mainly along its axis | Video 5 |
| Shaking horizontally | Same as above but with horizontal attachment | Video 6 |
| Rotating wheel | Arm attached to a revolvable bar/wheel | Video 7 |
| Rotating wheel II | Parallel wheel – arm arrangement | Video 8 |
| Rotating wheel III | Different rotation frequencies | Video 9 |
| Wiping table | Arm with brush starts to wipe a table | Video 10 |
| Wiping table modes | Different wiping patterns from reloaded controllers | Video 11 |
| Free | No external forces applied: pseudo-random sequences of reaching-type behavior | Video 12 |
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Video 1: Overview video summarizing the experimental results of the paper. This video provides a demonstration of the control paradigm applied to the tendon driven anthropomorphic arm. Compliant control self-organizes from a dynamical interplay between robot, environment and neural plasticity of the controller. [mp4 video file]
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Video 2: Handshake: Human-robot interaction by manually imposing a periodic movement. A longer version can be found here. [mp4 video file]
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Video 3: Bottle swing: Excitation of a circular pendulum mode. The suspended bottle, once exited to swing a little bit, excerts forces onto the arm, which are incoorporated into the controller throught the plasticity rule. This leads eventually to a coherent swinging motion. [mp4 video file]
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Video 4: Measuring the force feedback of the swinging bottle. The motors are stopped while recording spring forces of swinging suspended bottle. [mp4 video file]
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Video 5: Shaking vertically: A half filled bottle is vertically attached to the tip of the arm. Emergent shaking behavior of the bottle mainly along its axis. [mp4 video file]
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Video 6: Shaking horizontally: Same as above but with horizontal attachment. The main shaking direction is now horizontal. [mp4 video file]
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Video 7: Rotating wheel: Arm is attached to a revolvable bar/wheel. Initially the connection between the arm and the wheel was rather loose so that for small movements there is not reaction from the rotation of the wheel. After improving this connection, an initial push by the experimenter was sufficient for excite a stable rotation mode. [mp4 video file]
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Video 8: Rotating wheel II: Arm and wheel are now arranged in a parallel setup. After an initial help, a stable rotation behavior is observed. Later it is demonstrated that the system can be switched between forward and backward rotation mode. [mp4 video file]
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Video 9: Rotating wheel III: Different rotation frequencies By changing the time-delay d of the delay-sensors the prefered frequency of controller can be adjusted, resulting in different rotation velocities. [mp4 video file]
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Video 10: Wiping table: The arm with a brush starts to wipe a table. Through the combination of the restricting table surface and the manual force, the robot is driven into the two-dimensional wiping mode. Later in this video the robot is guided into a different behavior, which persists for a short time before it transisions to a new behavior. [mp4 video file]
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Video 11: Wiping table modes: Different wiping patterns from reloaded controllers. During earlier runs we took snapshots of the controller weights C when a new wiping mode occured. In this video we show that by simply reloaded the controllers (and keeping their weights fixed) the robot transitions smoothly into the respective attractor behavior. [mp4 video file]
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Video 12: Free: without external forces a pseudo-random sequences of reaching-type behavior may be observed. [mp4 video file]
This document was translated from LATEX by HEVEA.