Articulated Object Interaction in Unknown Scenes with Whole-Body Mobile Manipulation

Mittal, Mayank; Hoeller, David; Farshidian, Farbod; Hutter, Marco; Garg, Animesh

doi:10.1109/iros47612.2022.9981779

Cited by 39 publications

(4 citation statements)

References 30 publications

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“…Therefore, a specialized arm can be used to tackle complex real-world tasks such as rotating a handwheel, handling articulated objects, and unlatching a door. (Sleiman et al, 2021;Ferrolho et al, 2022;Mittal et al, 2022), which would be much harder to approach using locomotive legs. In addition, an onboard arm can reach the legs themselves, which may prove useful if the legs need to be repaired or untangled.…”

Section: Frontiers In Mechanical Engineeringmentioning

confidence: 99%

Legged robots for object manipulation: A review

et al. 2023

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Legged robots can have a unique role in manipulating objects in dynamic, human-centric, or otherwise inaccessible environments. Although most legged robotics research to date typically focuses on traversing these challenging environments, many legged platform demonstrations have also included “moving an object” as a way of doing tangible work. Legged robots can be designed to manipulate a particular type of object (e.g., a cardboard box, a soccer ball, or a larger piece of furniture), by themselves or collaboratively. The objective of this review is to collect and learn from these examples, to both organize the work done so far in the community and highlight interesting open avenues for future work. This review categorizes existing works into four main manipulation methods: object interactions without grasping, manipulation with walking legs, dedicated non-locomotive arms, and legged teams. Each method has different design and autonomy features, which are illustrated by available examples in the literature. Based on a few simplifying assumptions, we further provide quantitative comparisons for the range of possible relative sizes of the manipulated object with respect to the robot. Taken together, these examples suggest new directions for research in legged robot manipulation, such as multifunctional limbs, terrain modeling, or learning-based control, to support a number of new deployments in challenging indoor/outdoor scenarios in warehouses/construction sites, preserved natural areas, and especially for home robotics.

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Section: Frontiers In Mechanical Engineeringmentioning

confidence: 99%

Legged robots for object manipulation: A review

et al. 2023

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“…Stillman et al presented the Golem Krang [13], a bi-wheeled manipulator capable of balancing while performing heavy lifting. Other related works [14] have integrated vision pipelines to facilitate mobility and manipulation. While these studies show promising preliminary forms of DMM, they do do not leverage human adaptability, and are constrained in their capacity to modify the robot's posture to synergistically combine the robot's body and arms for force amplification.…”

Section: Related Workmentioning

confidence: 99%

Hands-free Telelocomotion of a Wheeled Humanoid

Purushottam¹,

Jung

Murphy

et al. 2022

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Humanoid robots have the potential to help human workers by realizing physically demanding manipulation tasks such as moving large boxes within warehouses. We define such tasks as Dynamic Mobile Manipulation (DMM). This paper presents a framework for DMM via whole-body teleoperation, built upon three key contributions: Firstly, a teleoperation framework employing a Human Machine Interface (HMI) and a bi-wheeled humanoid, SATYRR, is proposed. Secondly, the study introduces a dynamic locomotion mapping, utilizing human-robot reduced order models, and a kinematic retargeting strategy for manipulation tasks. Additionally, the paper discusses the role of whole-body haptic feedback for wheeled humanoid control. Finally, the system's effectiveness and mappings for DMM are validated through locomanipulation experiments and heavy box pushing tasks. Here we show two forms of DMM: grasping a target moving at an average speed of 0.4 m/s, and pushing boxes weighing up to 105% of the robot's weight. By simultaneously adjusting their pitch and using their arms, the pilot adjusts the robot pose to apply larger contact forces and move a heavy box at a constant velocity of 0.2 m/s.

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“…However, the complexity of viewpoint tracking is increased due to the additional redundant freedoms of the gimbal. Whole‐body motion control method based on model predictive control (MPC) is well‐developed for mobile manipulators (Chiu et al, 2022; Mittal et al, 2022; Pankert & Hutter, 2020) to track the reference trajectories of the end‐effector, but these robots have only worked on flat indoor grounds. Other studies have researched motion planning on rough terrains, which modeled the terrain data as soft‐constraints (Mastalli et al, 2020) or hard‐constraints (Fan et al, 2021) in an optimization problem to select a safe trajectory.…”

Section: Introductionmentioning

confidence: 99%

Whole‐body motion planning and tracking of a mobile robot with a gimbal RGB‐D camera for outdoor 3D exploration

Wang,

Chen,

2024

Journal of Field Robotics

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Autonomous exploration is a fundamental problem for certain applications of unmanned ground vehicles (UGVs). Depth cameras are widely used in exploring indoor and specific outdoor environments. However, existing methods suffer from inefficient and unstable performance of exploration in open outdoor environments. This study develops a framework to achieve fast and robust three‐dimensional exploration by UGVs with a gimbal camera in challenging outdoor environments. A hierarchical reactive planning approach based on a multilayered map is proposed to improve exploration efficiency. Additionally, an adaptive semantic mapping algorithm is proposed to more accurately and stably represent the environmental localization uncertainty. Localization uncertainty is integrated into the planning approach to decrease odometry drift and prevent localization failure, further enhancing the exploration robustness. A viewpoint tracking controller based on terrain‐aware model predictive control is proposed to guarantee the accuracy of the planned viewpoint tracking and to further improve the robustness of localization and exploration on rough terrains. Finally, several physical‐engine simulations and experiments in outdoor environments are performed. The comparisons to existing state‐of‐the‐art approaches have verified the effectiveness of the proposed approach. The code of our system will be available at https://github.com/HITSZ-NRSL/Open3DExplorer.git.

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Articulated Object Interaction in Unknown Scenes with Whole-Body Mobile Manipulation

Cited by 39 publications

References 30 publications

Legged robots for object manipulation: A review

Legged robots for object manipulation: A review

Hands-free Telelocomotion of a Wheeled Humanoid

Whole‐body motion planning and tracking of a mobile robot with a gimbal RGB‐D camera for outdoor 3D exploration

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