Papers by Kurniawan Wijaya
Modeling and predicting human behavior is in- dispensable when industrial robots interacting with... more Modeling and predicting human behavior is in- dispensable when industrial robots interacting with human operators are to be manipulated safely and efficiently. One challenge is that human operators tend to follow different motion patterns, depending on their intention and the struc- ture of the environment. This precludes the use of classical estimation techniques based on kinematic or dynamic models, especially for the purpose of long-term prediction. In this paper, we propose a method based on Hidden Markov Models to predict the region of the workspace that is possibly occupied by the human within a prediction horizon. In contrast to predictions in the form of single points such as most likely human positions as obtained from previous approaches, the regions obtained here may serve as safety constraints when the robot motion is planned or optimized. This way one avoids collisions with a probability not less than a predefined threshold. The practicability of our method is demonstrated by successfully and accurately predicting the motion of a human arm in two scenarios involving multiple motion patterns.
Recently, the problem of how to manipulate industrial robots that interact with human operators a... more Recently, the problem of how to manipulate industrial robots that interact with human operators attracts a lot of attention in robotics research. This interest stems from the insight that the integration of human operators into robot based manufacturing systems may increase productivity by combining the abilities of machines with those of humans. In such a Human-Robot-Interaction (HRI) setting, the challenge is to manipulate the robots both safely and efficiently. This paper proposes an online motion planning approach for robotic manipulators with HRI based on model predictive control (MPC) with embedded mixedinteger programming. Safety-relevant regions, which are potentially occupied by the human operators, are generated online using camera data and a knowledge-base of typical human motion patterns. These regions serve as constraints of the optimization problem solved online to generate control trajectories for the robot. As described in the last part of the paper, the proposed method is realized for a lab-scale HRI scenario.
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Papers by Kurniawan Wijaya