A Collision-Free MPC for Whole-Body Dynamic Locomotion and Manipulation

Chiu, Jen-Hwey; Sleiman, Jean-Pierre; Mittal, Mayank; Farshidian, Farbod; Hutter, Marco

doi:10.1109/icra46639.2022.9812280

Cited by 29 publications

(12 citation statements)

References 35 publications

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“…The advancement of model predictive control (MPC) for legged robots [4], [9] has facilitated the creation of realtime control systems that can execute diverse walking gaits. Most research on quadruped robots has concentrated on locomotion [7], [1], and loco-manipulation [2], [14], [21], [13], [19], [5] by a single robot. The approaches are even extended to the problem with significant uncertainty in robot model [16] as well as manipulating an object with unknown property [17].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Force-based Control for Legged Robots

Sombolestan

Chen

Nguyen

2021

2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Despite the potential benefits of collaborative robots, effective manipulation tasks with quadruped robots remain difficult to realize. In this paper, we propose a hierarchical control system that can handle real-world collaborative manipulation tasks, including uncertainties arising from object properties, shape, and terrain. Our approach consists of three levels of controllers. Firstly, an adaptive controller computes the required force and moment for object manipulation without prior knowledge of the object's properties and terrain. The computed force and moment are then optimally distributed between the team of quadruped robots using a Quadratic Programming (QP)-based controller. This QP-based controller optimizes each robot's contact point location with the object while satisfying constraints associated with robot-object contact. Finally, a decentralized loco-manipulation controller is designed for each robot to apply manipulation force while maintaining the robot's stability. We successfully validated our approach in a high-fidelity simulation environment where a team of quadruped robots manipulated an unknown object weighing up to 18 kg on different terrains while following the desired trajectory.

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Section: Introductionmentioning

confidence: 99%

Adaptive Force-based Control for Legged Robots

Sombolestan

Chen

Nguyen

2021

2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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“…This PDF file includes: Results Methods Tables S1 to S6 Figs. S1 to S13 References (65)(66)(67)(68)(69)(70)(71)(72)(73)(74)(75)(76)(77)(78)(79)(80)(81)(82)(83) Other Supplementary Material for this manuscript includes the following: Movies S1 and S2…”

Section: Supplementary Materialsmentioning

confidence: 99%

Scientific exploration of challenging planetary analog environments with a team of legged robots

et al. 2023

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The interest in exploring planetary bodies for scientific investigation and in situ resource utilization is ever-rising. Yet, many sites of interest are inaccessible to state-of-the-art planetary exploration robots because of the robots’ inability to traverse steep slopes, unstructured terrain, and loose soil. In addition, current single-robot approaches only allow a limited exploration speed and a single set of skills. Here, we present a team of legged robots with complementary skills for exploration missions in challenging planetary analog environments. We equipped the robots with an efficient locomotion controller, a mapping pipeline for online and postmission visualization, instance segmentation to highlight scientific targets, and scientific instruments for remote and in situ investigation. Furthermore, we integrated a robotic arm on one of the robots to enable high-precision measurements. Legged robots can swiftly navigate representative terrains, such as granular slopes beyond 25°, loose soil, and unstructured terrain, highlighting their advantages compared with wheeled rover systems. We successfully verified the approach in analog deployments at the Beyond Gravity ExoMars rover test bed, in a quarry in Switzerland, and at the Space Resources Challenge in Luxembourg. Our results show that a team of legged robots with advanced locomotion, perception, and measurement skills, as well as task-level autonomy, can conduct successful, effective missions in a short time. Our approach enables the scientific exploration of planetary target sites that are currently out of human and robotic reach.

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“…Because of the generic contact classification discussed earlier, the same constraint set would be applicable to diverse scenarios involving arbitrary mobile manipulators or articulated objects. Besides standard continuously active constraints enforcing system operational limits, workspace limits, and collision avoidance (89), we introduced a collection of contact-driven constraints that are parameterized by the manipulation mode. The mode can be readily extracted from the current contact state s k and the contact switching action a k .…”

Section: Contact-driven Trajectory Optimizationmentioning

confidence: 99%

Versatile multicontact planning and control for legged loco-manipulation

2023

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Loco-manipulation planning skills are pivotal for expanding the utility of robots in everyday environments. These skills can be assessed on the basis of a system’s ability to coordinate complex holistic movements and multiple contact interactions when solving different tasks. However, existing approaches have been merely able to shape such behaviors with hand-crafted state machines, densely engineered rewards, or prerecorded expert demonstrations. Here, we propose a minimally guided framework that automatically discovers whole-body trajectories jointly with contact schedules for solving general loco-manipulation tasks in premodeled environments. The key insight is that multimodal problems of this nature can be formulated and treated within the context of integrated task and motion planning (TAMP). An effective bilevel search strategy was achieved by incorporating domain-specific rules and adequately combining the strengths of different planning techniques: trajectory optimization and informed graph search coupled with sampling-based planning. We showcase emergent behaviors for a quadrupedal mobile manipulator exploiting both prehensile and nonprehensile interactions to perform real-world tasks such as opening/closing heavy dishwashers and traversing spring-loaded doors. These behaviors were also deployed on the real system using a two-layer whole-body tracking controller.

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A Collision-Free MPC for Whole-Body Dynamic Locomotion and Manipulation

Cited by 29 publications

References 35 publications

Adaptive Force-based Control for Legged Robots

Adaptive Force-based Control for Legged Robots

Scientific exploration of challenging planetary analog environments with a team of legged robots

Versatile multicontact planning and control for legged loco-manipulation

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