Supervised footstep planning for humanoid robots in rough terrain tasks using a black box walking controller

Stumpf, Alexander; Kohlbrecher, Stefan; Conner, David C.; Stryk, Oskar von

doi:10.1109/humanoids.2014.7041374

Cited by 33 publications

(26 citation statements)

References 17 publications

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“…Stumpf et al propose 2.5D height maps and are capable of planning longer footstep paths also on inclined terrain. However, instead of detecting planar regions they use ground contact estimates to ensure stability [5]. In our approach, we combine 2.5D height maps and fast segmentation of planar regions based on plane normals and region growing.…”

Section: Related Workmentioning

confidence: 99%

“…Due to the calculation of the 2D cost map used for collision checking of the footsteps and the exploration of the search space as defined by a given set of possible footsteps, these algorithms are computationally expensive. Other approaches use 2.5D height maps or 3D maps and directly plan footsteps upon convenient walking regions [4], [5]. However, the amount of data to be processed leads to run times that are generally not suitable for dynamic environments.…”

Section: Introductionmentioning

confidence: 99%

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Real-time footstep planning using a geometric approach

Karkowski

Bennewitz

2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

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To this date, many footstep planning systems rely on external sensors for mapping and traversability analysis or on computationally expensive algorithms that do not allow for real-time calculations. In this paper, we present an approach that analyzes the environment in the vicinity of the robot with an onboard RGBD camera while computing local footstep plans in real time. We achieve this by combining the advantages of grid-based height maps, fast planar region segmentation, and a systematic local footstep search to a local goal point. Using a single CPU core, a full mapping and planning cycle only takes 18 ms on average and thus presents an important step to autonomous humanoid robots in dynamic environments that only rely on their onboard hardware.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Real-time footstep planning using a geometric approach

Karkowski

Bennewitz

2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

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“…As a result of the 2013 DARPA Robotics Challenge Trials several teams presented their frameworks for walking in uneven terrain [22], [23]. While the algorithm presented by [22] relies on user input to define obstacle-free regions, the foot-step planner of [23] uses a height map based on point cloud processing. However, the walking controller and the swing-foot movements are not taken into account.…”

Section: Related Workmentioning

confidence: 99%

Real-time pattern generation among obstacles for biped robots

Hildebrandt

Wahrmann

Wittmann

et al. 2015

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Abstract-In this paper we present a step-planner embedded in a framework which enables a humanoid robot to navigate among obstacles, exploiting its overall capacities. The system allows the robot to react to changes of user input in real-time while walking at reasonable speeds. The proposed method relies neither on external sensors nor on color coding or textured surfaces. The key idea is to use a fast collision model based on swept-sphere-volumes (SSVs) for real-time generation of collision-free footsteps and whole-body trajectories. Using a SSV-based 3D approximation in all control modules enables the robot to avoid collisions with itself and the environment. Obstacles are detected with an on-board RGB-D sensor while the robot navigates through an environment which is not known in advance. A step-planner reacts to high-level user commands like desired velocity and direction within less than a step. Instead of investigating only the footholds an articulated 3D approximation of the lower leg and the foot is considered to find feasible and optimal footstep locations. Additionally, it provides an initial solution for the swing-foot movement. Final, Collision-free swing-foot trajectories are created in real-time in the feedback control layer using all the foot's degrees of freedom. We validated this approach in experiments with our robot Lola.

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“…To achieve dynamic stable walking on rough ground, Nishiwaki et al designed a high-frequency pattern generator which considered the current actual motion of the robot as the initial conditions of each generation [15]. In [16], a graph-based footstep planning approach was proposed to generate the whole step sequences in rough terrain scenarios using a black box walking controller. In [17], the preplanned trajectories were modified online to guarantee a smooth landing after the detection of the foot touching the uneven ground.…”

Section: Introductionmentioning

confidence: 99%

Design and Experimental Development of a Pneumatic Stiffness Adjustable Foot System for Biped Robots Adaptable to Bumps on the Ground

Zang

Liu

et al. 2017

Applied Sciences

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Walking on rough terrains still remains a challenge that needs to be addressed for biped robots because the unevenness on the ground can easily disrupt the walking stability. This paper proposes a novel foot system with passively adjustable stiffness for biped robots which is adaptable to small-sized bumps on the ground. The robotic foot is developed by attaching eight pneumatic variable stiffness units to the sole separately and symmetrically. Each variable stiffness unit mainly consists of a pneumatic bladder and a mechanical reversing valve. When walking on rough ground, the pneumatic bladders in contact with bumps are compressed, and the corresponding reversing valves are triggered to expel out the air, enabling the pneumatic bladders to adapt to the bumps with low stiffness; while the other pneumatic bladders remain rigid and maintain stable contact with the ground, providing support to the biped robot. The performances of the proposed foot system, including the variable stiffness mechanism, the adaptability on the bumps of different heights, and the application on a biped robot prototype are demonstrated by various experiments.

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Supervised footstep planning for humanoid robots in rough terrain tasks using a black box walking controller

Cited by 33 publications

References 17 publications

Real-time footstep planning using a geometric approach

Real-time footstep planning using a geometric approach

Real-time pattern generation among obstacles for biped robots

Design and Experimental Development of a Pneumatic Stiffness Adjustable Foot System for Biped Robots Adaptable to Bumps on the Ground

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