Hexapod robots

AMOS

 

AMOS (Advanced Mobility Sensor Driven-Walking Device) is the 6-legged walking robot which mimics the structures of walking animals, i.e. cockoach. This robot is controlled by neural control and learning mechanisms which allow it to autonomously perform a broad behavioral repertoire including foothold searching, elevator reflex (swinging a leg over obstacles), self-protective reflex (standing in an upside-down position), obstacle avoidance, auditory- and wind-evoked escape responses, phototaxis (turn towards a light source), climbing over obstacles, and five different gaits. Furthermore it can learn to adapt its walking pattern to new situations. This robot can serve as a hardware platform for experiments concerning the function of a neural perception-action system.

The performance of AMOS can be seen at AMOS page.

AMOSII

AMOSII(Advanced Mobility Sensor Driven-Walking Device version II) is a new version of AMOS. It is a biologically inspired hardware platform. It was developed in collaboration between Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS and the Computational Neuroscience Group of Prof. Woergoetter. It is used to study the coordination of many degrees of freedom, to perform experiments with neural control, memory, and learning and to develop artificial perceptionaction systems employing embodied control techniques. AMOSII can carry a maximum payload of 6 kg while walking. The size of AMOSII is 30 cm wide, 40 cm long, 20 cm high. AMOSII has a number of proprioceptive and exteroceptive sensors, e.g., angle sensors, force sensors, current sensors, light sensors, infrared sensors, ultrasonic sensors. These sensors allow AMOSII to autonomously perform a broad behavioral repertoire including foothold searching, elevator reflex (swinging a leg over obstacles), self-protective reflex (standing in an upside-down position), obstacle avoidance, escape responses, phototaxis (turn towards a light source), climbing over obstacles, and five different gaits. Furthermore it can learn to adapt its walking pattern to a new situation.

The performance of AMOSII can be seen at AMOSII page.