Towards More Possibilities: Motion Planning and Control for Hybrid Locomotion of Wheeled-Legged Robots

Sun, J.; You, Yangwei; Zhao, Xi; Adiwahono, Albertus Hendrawan; Chew, Chee-Meng

doi:10.1109/lra.2020.2979626

Cited by 25 publications

(12 citation statements)

References 28 publications

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“…Similar results can be observed with the wheeled-legged robot Pholus. In Sun et al (2020), a control framework is proposed for hybrid locomotion built on a hierarchical structure based on: hybrid footstep placement planning, Center of Mass trajectory optimization and whole-body control. In particular, the foot placement planning is executed considering a set of motion modalities defined: driving, walking or, more generally, hybrid modes.…”

Section: Related Workmentioning

confidence: 99%

Autonomous Obstacle Crossing Strategies for the Hybrid Wheeled-Legged Robot Centauro

et al. 2021

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The development of autonomous legged/wheeled robots with the ability to navigate and execute tasks in unstructured environments is a well-known research challenge. In this work we introduce a methodology that permits a hybrid legged/wheeled platform to realize terrain traversing functionalities that are adaptable, extendable and can be autonomously selected and regulated based on the geometry of the perceived ground and associated obstacles. The proposed methodology makes use of a set of terrain traversing primitive behaviors that are used to perform driving, stepping on, down and over and can be adapted, based on the ground and obstacle geometry and dimensions. The terrain geometrical properties are first obtained by a perception module, which makes use of point cloud data coming from the LiDAR sensor to segment the terrain in front of the robot, identifying possible gaps or obstacles on the ground. Using these parameters the selection and adaption of the most appropriate traversing behavior is made in an autonomous manner. Traversing behaviors can be also serialized in a different order to synthesise more complex terrain crossing plans over paths of diverse geometry. Furthermore, the proposed methodology is easily extendable by incorporating additional primitive traversing behaviors into the robot mobility framework and in such a way more complex terrain negotiation capabilities can be eventually realized in an add-on fashion. The pipeline of the above methodology was initially implemented and validated on a Gazebo simulation environment. It was then ported and verified on the CENTAURO robot enabling the robot to successfully negotiate terrains of diverse geometry and size using the terrain traversing primitives.

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Section: Related Workmentioning

confidence: 99%

Autonomous Obstacle Crossing Strategies for the Hybrid Wheeled-Legged Robot Centauro

et al. 2021

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“…On the other hand, wheeled robots are not as mobile as their legged counterparts, but they are far more energyefficient. By combining legs and wheels into a hybrid system, roboticists have tried to keep the best characteristics of legged and wheeled systems [1], [2], [3]. Unfortunately, increased flexibility comes with an increase in complexity, especially true for motion planning since the combinatorial aspect of legged robots (contact schedule) is combined with wheeled robots' non-holonomic nature (rolling constraints).…”

Section: Introductionmentioning

confidence: 99%

Combined Sampling and Optimization Based Planning for Legged-Wheeled Robots

Jelavić¹,

Farshidian²,

Hutter³

2021

Preprint

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Planning for legged-wheeled machines is typically done using trajectory optimization because of many degrees of freedom, thus rendering legged-wheeled planners prone to falling prey to bad local minima. We present a combined sampling and optimization-based planning approach that can cope with challenging terrain. The sampling-based stage computes whole-body configurations and contact schedule, which speeds up the optimization convergence. The optimization-based stage ensures that all the system constraints, such as nonholonomic rolling constraints, are satisfied. The evaluations show the importance of good initial guesses for optimization. Furthermore, they suggest that terrain/collision (avoidance) constraints are more challenging than the robot model's constraints. Lastly, we extend the optimization to handle general terrain representations in the form of elevation maps.

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“…In contrast, a recent work presented in [17] introduces a hierarchical control framework for the Pholus robot designed to perform hybrid locomotion in uneven terrain, taking into account the terrain height changes in the motion planning. Experimental results shows the robot overcoming thin obstacles and steps with statically stable hybrid motions at low speeds.…”

Section: Introductionmentioning

confidence: 99%

Trajectory Optimization for Hybrid Wheeled-Legged Robots in Challenging Terrain

Medeiros

Meggiolaro

2020

Anais Estendidos Do XII Simpósio Brasileiro De Robótica E XVII Simpósio Latino Americano De Robótica (SBR/LARS Estendido 2020)

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Wheeled-legged robots are a promising solution for agile locomotion in challenging terrain, combining the speed of the wheels with the ability of the legs to cope with unstructured environments. This paper presents a trajectory optimization framework that allows wheeled-legged robots to navigate in challenging terrain, e.g., steps, slopes, gaps, while negotiating these obstacles with dynamic motions. The framework generates the robot’s base motion as well as the wheels’ positions and contact forces along the trajectory, accounting for the terrain map and the dynamics of the robot. The knowledge of the terrain map allows the optimizer to generate feasible motions for obstacle negotiation in a dynamic manner, at higher speeds. To take full advantage of the hybrid nature of wheeled-legged robots, driving and stepping motions are both considered in a single planning problem that can generate trajectories with purely driving motions or hybrid driving-stepping motions. The optimization is formulated as a Nonlinear Programming Problem (NLP) employing a phase-based parametrization to optimize over the wheels’ motion and contact forces. The reference trajectories are tracked by a hierarchical whole-body controller that computes the torque actuation commands for the robot. The motion plans are verified on the quadrupedal robot ANYmal equipped with non-steerable torque-controlled wheels in simulations and experimental tests. Agile hybrid motions are demonstrated in simulations with discontinuous obstacles, such as floating steps and gaps, at an average speed of 0.75 m/s.

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Towards More Possibilities: Motion Planning and Control for Hybrid Locomotion of Wheeled-Legged Robots

Cited by 25 publications

References 28 publications

Autonomous Obstacle Crossing Strategies for the Hybrid Wheeled-Legged Robot Centauro

Autonomous Obstacle Crossing Strategies for the Hybrid Wheeled-Legged Robot Centauro

Combined Sampling and Optimization Based Planning for Legged-Wheeled Robots

Trajectory Optimization for Hybrid Wheeled-Legged Robots in Challenging Terrain

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