Abstract
Legged and wheeled locomotion are two standard methods used by robots to perform navigation. Combining them to create a hybrid legged-wheeled locomotion results in increased speed, agility, and reconfigurability for the robot, allowing it to traverse a multitude of environments. The CENTAURO robot has these advantages, but they are accompanied by a higher-dimensional search space for formulating autonomous economical motion plans, especially in cluttered environments. In this article, we first review our previously presented legged-wheeled footprint reconfiguring global planner. We describe the two incremental prototypes, where the primary goal of the algorithms is to reduce the search space of possible footprints such that plans that expand the robot over the low-lying wide obstacles or narrow into passages can be computed with speed and efficiency. The planner also considers the cost of avoiding obstacles versus negotiating them by expanding over them. The second part of this article presents our new work on local obstacle pushing, which further increases the number of tight scenarios the planner can solve. The goal of the new local push-planner is to place any movable obstacle of unknown mass and inertial properties, obstructing the previously planned trajectory from our global planner, to a location devoid of obstruction. This is done while minimising the distance traveled by the robot, the distance the object is pushed, and its rotation caused by the push. Together, the local and global planners form a major part of the agile reconfigurable navigation suite for the legged-wheeled hybrid CENTAURO robot.
Highlights
Mobile robots often need the speed of wheeled rolling motion and the agility of legged locomotion
THE CENTAURO ROBOT Given that the hybrid wheeled-legged robot CENTAURO, will be used in this paper, we firstly introduce it
EXPERIMENTAL AND SIMULATION RESULTS we first briefly discuss the experimental results obtained on the real CENTAURO robot using the plans from Prototype 1 and Prototype 2 of the global planner algorithms, described in Sec
Summary
Mobile robots often need the speed of wheeled rolling motion and the agility of legged locomotion. We use a hybrid quadruped robot (CENTAURO [1] in Fig. 1) that has wheels at the end of each foot In this way, the robot can roll, but in the same time, it can alter its height and the configuration and orientation of its legs (i.e., its footprint polygon) to walk in narrow passages, over obstacles, or even push objects away in order to create free space. The robot can roll, but in the same time, it can alter its height and the configuration and orientation of its legs (i.e., its footprint polygon) to walk in narrow passages, over obstacles, or even push objects away in order to create free space The control of such hybrid systems might be challenging, given that it might require switching between rolling and stepping control, with heavy path planning computations.
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