Topology Representing Network for Sensor-Based Robot Motion Planning
نویسندگان
چکیده
We present a framework for sensor-based motion planning of robotic manipulators using a topology representing network (TRN). Exploiting the perfectly topology preserving features of the network, the algorithm learns the representation of the Perceptual Control Manifold (PCM), a recently introduced concept for motion planning. This concept allows sensors to be integrated into robot motion planning. Besides a demonstration of the technical feasibility of motion planning through perfectly topology preserving maps the capabilities of this approach within an engineering framework, namely the implementation on a pneumatically driven robot arm (SoftArm), are demonstrated.
منابع مشابه
Motion Planning of a Pneumatic
Integration of sensing and motion planning plays a crucial role in autonomous robot operation. We present a framework for sensor-based robot motion planning that uses learning to handle arbitrarily conngured sensors and robots. The theoretical basis of this approach is the concept of the Perceptual Control Manifold that extends the notion of the robot connguration space to include sensor space....
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