Planning and execution of dynamic whole-body locomotion for a hydraulic quadruped on challenging terrain

Winkler, Alexander; Mastalli, Carlos; Havoutis, Ioannis; Focchi, Michele; Caldwell, Darwin G.; Semini, Claudio

doi:10.1109/icra.2015.7139916

Cited by 104 publications

(108 citation statements)

References 18 publications

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“…To realize the low-dimensional plan, the controller selects appropriate torque commands, which are computed by the combination of a trunk controller with a joint-space torque controller. The proposed trajectory optimization method increases the locomotion capabilities of our legged robot, compared to our previous framework [6] [7]. As shown in Fig.…”

Section: Introductionmentioning

confidence: 72%

“…Compared with our previous work [6], we increased the walking velocity by approximately 80%, while also modulating the trunk attitude. Furthermore, the foothold error is on average less than 2 cm, which increases the success rate of the stepping stones trials to 90%; an increment of 30% when compared with our previous work [6]. Despite these improvements, the stochasticbased optimization tends to increase the computation time due to the non-convex nature of the problem.…”

Section: B Locomotion On Challenging Terrainmentioning

confidence: 82%

“…1) CoM motion: In our previous work [6], we showed that for fixed step durations, the CoP movement is approximately linear, i.e. :…”

Section: A Preview Modelmentioning

confidence: 99%

“…[15]. These approaches often decouple the foothold selection from the CoM planning, assuming a fixed step duration, and do not consider attitude planning [6][8] [9]. However, in field applications, the terrain conditions are often rough and irregular.…”

Section: Related Workmentioning

confidence: 99%

“…A number of successful control architectures [6][8] [9][10] [11] that plan and execute footsteps for traversing such terrain have been proposed. Some avoid global footstep planning by simply choosing the next best reachable footholds [11], while others plan the complete footstep sequence from start to goal [10] [12].…”

Section: Related Workmentioning

confidence: 99%

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Trajectory and foothold optimization using low-dimensional models for rough terrain locomotion

Mastalli

Focchi

Havoutis

et al. 2017

2017 IEEE International Conference on Robotics and Automation (ICRA)

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Abstract-We present a trajectory optimization framework for legged locomotion on rough terrain. We jointly optimize the center of mass motion and the foothold locations, while considering terrain conditions. We use a terrain costmap to quantify the desirability of a foothold location. We increase the gait's adaptability to the terrain by optimizing the step phase duration and modulating the trunk attitude, resulting in motions with guaranteed stability. We show that the combination of parametric models, stochastic-based exploration and receding horizon planning allows us to handle the many local minima associated with different terrain conditions and walking patterns. This combination delivers robust motion plans without the need for warm-starting. Moreover, we use soft-constraints to allow for increased flexibility when searching in the cost landscape of our problem. We showcase the performance of our trajectory optimization framework on multiple terrain conditions and validate our method in realistic simulation scenarios and experimental trials on a hydraulic, torque controlled quadruped robot.

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Section: Introductionmentioning

confidence: 72%

Section: B Locomotion On Challenging Terrainmentioning

confidence: 82%

“…1) CoM motion: In our previous work [6], we showed that for fixed step durations, the CoP movement is approximately linear, i.e. :…”

Section: A Preview Modelmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 3 more Smart Citations

Trajectory and foothold optimization using low-dimensional models for rough terrain locomotion

Mastalli

Focchi

Havoutis

et al. 2017

2017 IEEE International Conference on Robotics and Automation (ICRA)

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Whole‐body motion planning and control of a quadruped robot for challenging terrain

Chen

Rong

et al. 2023

Journal of Field Robotics

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Quadruped robots working in jungles, mountains or factories should be able to move through challenging scenarios. In this paper, we present a control framework for quadruped robots walking over rough terrain. The planner plans the trajectory of the robot's center of gravity by using the normalized energy stability criterion, which ensures that the robot is in the most stable state. A contact detection algorithm based on the probabilistic contact model is presented, which implements eventbased state switching of the quadruped robot legs. And an on-line detection of contact force based on generalized momentum is also showed, which improves the accuracy of proprioceptive force estimation. A controller combining whole body control and virtual model control is proposed to achieve precise trajectory tracking and active compliance with environment interaction. Without any knowledge of the environment, the experiments of the quadruped robot SDUQuad-144 climbs over significant obstacles such as 38 cm high steps and 22.5 cm high stairs are designed to verify the feasibility of the proposed method.

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Heuristic Planning for Rough Terrain Locomotion in Presence of External Disturbances and Variable Perception Quality

Focchi

Orsolino

Camurri

et al. 2019

Springer Tracts in Advanced Robotics

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The quality of visual feedback can vary significantly on a legged robot meant to traverse unknown and unstructured terrains. The map of the environment, acquired with online state-of-the-art algorithms, often degrades after a few steps, due to sensing inaccuracies, slippage and unexpected disturbances. If a locomotion algorithm is not designed to deal with this degradation, its planned trajectories might endup to be inconsistent in reality. In this work, we propose a heuristic-based planning approach that enables a quadruped robot to successfully traverse a significantly rough terrain (e.g. stones up to 10 cm of diameter), in absence of visual feedback. When available, the approach allows also to leverage the visual feedback (e.g. to enhance the stepping strategy) in multiple ways, according to the quality of the 3D map. The proposed framework also includes reflexes, triggered in specific situations, and the possibility to estimate online an unknown time-varying disturbance and compensate for it. We demonstrate the effectiveness of the approach with experiments performed on our quadruped robot HyQ (85 kg), traversing different terrains, such as: ramps, rocks, bricks, pallets and stairs. We also demonstrate the capability to estimate and compensate for external disturbances by showing the robot walking up a ramp while pulling a cart attached to its back.

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Planning and execution of dynamic whole-body locomotion for a hydraulic quadruped on challenging terrain

Cited by 104 publications

References 18 publications

Trajectory and foothold optimization using low-dimensional models for rough terrain locomotion

Trajectory and foothold optimization using low-dimensional models for rough terrain locomotion

Whole‐body motion planning and control of a quadruped robot for challenging terrain

Heuristic Planning for Rough Terrain Locomotion in Presence of External Disturbances and Variable Perception Quality

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