RoboHike: Autonomous Quadrupedal Robot Navigation and Hiking in Challenging Rough Terrains

Quadrupedal robots are gaining important capabilities, especially over the past decade, due to the rapid advancements in mechatronics, control, and planning.

In scenarios that robots need to operate for either inspecting hard-to-reach areas or aiding humans in dangerous and hazardous environments, quadrupedal robots could be ideal due to their ability to deal with sparse footholds in a safe and energy efficient way.

To date, quadrupedal robots are able to traverse some types of rough terrain, using usually traditional control and perception methods.

However, their mobility is still far behind their natural counterparts, especially in cases that the environment is dynamically changing.

Tasks such as navigating and hiking rough or rocky trails, where the environment itself is uncertain, not fully perceived, and potentially dynamically changing, remain central challenges in legged robot locomotion.

RoboHike aims at introducing and developing novel high level and platform-agnostic perception and learning approaches for modeling, identifying, and mapping footholds for quadrupedal robots, such that it would be possible to achieve fast, robust, and reliable navigation and hiking skills on challenging terrains.

In particular, it aims at combining various sensing systems, such as proprioceptive (e.g., inertia, speed, or joint torques) and exteroceptive (e.g., visual, range, event, or foot's force contact data) perception to reconstruct the environment and handle the uncertainty of potentially missing or inaccurate data, before and during locomotion, especially for dynamically changing terrains.

This will enable novel footstep planning and robot localization in the environment.

Analytic and (self-supervised and reinforcement) learning methods will leverage multi-modal sensing to allow quadrupedal robots mimic the way that animals plan footsteps when learning to walk.

The developed methods will be validated experimentally on several full-size quadrupedal robots, in academic and industrial real-world use cases, for tasks such as inspection, patrolling, and maintenance.

RoboHike will work towards the next-generation autonomous robotic systems in construction fields, oil&gas sites, or damaged sites after a man-made/natural disaster, where efficient navigation is required, and rough/rocky terrain, industrial stairs, pipes, and narrow passages may exist.

The vision is to endow quadrupeds with environment cognition for the benefit of the public in autonomizing manual labor of hard or dangerous tasks.

The impact is expected to be high in the national and industrial sectors for automated inspection, monitoring, maintenance, and disaster innervations, where terrain is arduous and the requirement for timely intervention is paramount.

We intend to construct publicly shared benchmark datasets on challenging trails, bringing in this way the robotics community several steps forward in robot locomotion by enabling robots to work on challenging grounds.