Quadruped locomotion is challenging for many learning-based algorithms. This is because it
requires tedious manual tuning to cope with different types of terrains and is difficult to …

Biological motor control mechanisms (eg, central pattern generators (CPGs), sensory
feedback, reflexes, and motor learning) play a crucial role in the adaptive locomotion of …

Introduction Animals such as cattle can achieve versatile and elegant behaviors through
automatic sensorimotor coordination. Their self-organized movements convey an …

ABSTRACT A limbed climbing robot can traverse uneven and steep terrain, such as
Lunar/Martian caves. Towards the autonomous operation of the robot, we first present a …

In the pursuit of a fully autonomous learning agent able to interact, move, and be useful in
the real world, two fundamental problems are path planning and motion control, and user …

In this paper, we present an approach for the learning of a visuomotor system for a robotic
rover using reinforcement learning (RL) within a simulation that combines both …

Reinforcement learning (RL) is a promising field to enhance robotic autonomy and decision
making capabilities for space robotics, something which is challenging with traditional …