A Unified MPC Framework for Whole-Body Dynamic Locomotion and Manipulation

Sleiman, Jean-Pierre; Farshidian, Farbod; Minniti, Maria Vittoria; Hutter, Marco

doi:10.1109/lra.2021.3068908

Cited by 142 publications

(75 citation statements)

References 27 publications

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“…We use a quadratic cost function where we encode the pushing task by setting a high weight on the object's deviation from the desired position. Moreover, we introduce a set of locomotion and manipulation-related state-input equality constraints that are defined at the level of the different contact points [7]. As for the arm torque limits, those are specified as follows: −τ max ≤ J T ca f ca ≤ τ max , where J ca and f ca are the arm contact Jacobian and end-effector contact forces, respectively.…”

Section: Quadrupedal Mobile Manipulatormentioning

confidence: 99%

“…Its ability to encode complex high-level tasks in simple and intuitive cost functions, while accounting for system constraints, has made it quite compelling in the robotics community. For instance, with regards to locomotion research, this approach has proven its effectiveness in generating dynamic motions for highly articulated underactuated machines such as humanoids [1], [2] or quadrupeds [3]- [7]. Fundamentally, MPC operates by repeatedly solving a finite-horizon optimal control problem (OCP) in a receding-horizon fashion.…”

Section: Introductionmentioning

confidence: 99%

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Constraint Handling in Continuous-Time DDP-Based Model Predictive Control

Sleiman

Farshidian

Hutter

2021

2021 IEEE International Conference on Robotics and Automation (ICRA)

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The Sequential Linear Quadratic (SLQ) algorithm is a continuous-time version of the well-known Differential Dynamic Programming (DDP) technique with a Gauss-Newton Hessian approximation. This family of methods has gained popularity in the robotics community due to its efficiency in solving complex trajectory optimization problems. However, one major drawback of DDP-based formulations is their inability to properly incorporate path constraints. In this paper, we address this issue by devising a constrained SLQ algorithm that handles a mixture of constraints with a previously implemented projection technique and a new augmented-Lagrangian approach. By providing an appropriate multiplier update law, and by solving a single inner and outer loop iteration, we are able to retrieve suboptimal solutions at rates suitable for real-time model-predictive control applications. We particularly focus on the inequality-constrained case, where three augmented-Lagrangian penalty functions are introduced, along with their corresponding multiplier update rules. These are then benchmarked against a relaxed log-barrier formulation in a cart-pole swing up example, an obstacle-avoidance task, and an objectpushing task with a quadrupedal mobile manipulator.

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Section: Quadrupedal Mobile Manipulatormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Constraint Handling in Continuous-Time DDP-Based Model Predictive Control

Sleiman

Farshidian

Hutter

2021

2021 IEEE International Conference on Robotics and Automation (ICRA)

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“…The priorities of each task are reported in Table I and will be discussed later in this section. It is worth mentioning that the reference commands from the master device are not directly sent to the whole-body controller, but are given as inputs to an intermediate motion planner [19]. Briefly, this planner solves a model predictive control (MPC) problem to generate optimal motion references for the robot's base and limbs.…”

Section: Hybrid Teleoperation Controlmentioning

confidence: 99%

“…where J T uxy includes the first two rows of (J T cu ), and ẋs is the base velocity. Using (9), we can rewrite (19) as:…”

Section: B Base Velocity Controlmentioning

confidence: 99%

Passivity-based control for haptic teleoperation of a legged manipulator in presence of time-delays

Risiglione

Sleiman

Minniti

et al. 2021

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

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When dealing with the haptic teleoperation of multi-limbed mobile manipulators, the problem of mitigating the destabilizing effects arising from the communication link between the haptic device and the remote robot has not been properly addressed. In this work, we propose a passive control architecture to haptically teleoperate a legged mobile manipulator, while remaining stable in the presence of time delays and frequency mismatches in the master and slave controllers. At the master side, a discrete-time energy modulation of the control input is proposed. At the slave side, passivity constraints are included in an optimization-based whole-body controller to satisfy the energy limitations. A hybrid teleoperation scheme allows the human operator to remotely operate the robot's endeffector while in stance mode, and its base velocity in locomotion mode. The resulting control architecture is demonstrated on a quadrupedal robot with an artificial delay added to the network.

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“…A unified model predictive control (MPC) framework was proposed, which plans the whole body motion/force trajectory task and combines dynamic motion and manipulation. Additionally, the robustness to model mismatch and external interference was verified by pushing/pulling a heavy resistance gate [ 15 ]. The above-mentioned quadruped robot with a manipulator has relatively stable coordinated motion and simple operation behavior, and it does not show dynamic motion ability.…”

Section: Introductionmentioning

confidence: 99%

Bio-Inspired Take-Off Maneuver and Control in Vertical Jumping for Quadruped Robot with Manipulator

et al. 2021

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The jumping motion of legged robots is an effective way to overcome obstacles in the rugged microgravity planetary exploration environment. At the same time, a quadruped robot with a manipulator can achieve operational tasks during movement, which is more practical. However, the additional manipulator will restrict the jumping ability of the quadruped robot due to the increase in the weight of the system, and more active degrees of freedom will increase the control complexity. To improve the jumping height of a quadruped robot with a manipulator, a bio-inspired take-off maneuver based on the coordination of upper and lower limbs is proposed in this paper. The kinetic energy and potential energy of the system are increased by driving the manipulator-end (ME) to swing upward, and the torso driven by the legs will delay reaching the required peak speed due to the additional load caused by the accelerated ME. When the acceleration of ME is less than zero, it will pull the body upward, which reduces the peak power of the leg joints. Therefore, the jumping ability of the system is improved. To realize continuous and stable jumping, a control framework based on whole-body control was established, in which the quadruped robot with a manipulator was a simplified floating seven-link model, and the hierarchical optimization was used to solve the target joint torques. This method greatly simplifies the dynamic model and is convenient for calculation. Finally, the jumping simulations in different gravity environments and a 15° slope were performed. The jump heights have all been improved after adding the arm swing, which verified the superiority of the bio-inspired take-off maneuver proposed in this paper. Furthermore, the stability of the jumping control method was testified by the continuous and stable jumping.

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A Unified MPC Framework for Whole-Body Dynamic Locomotion and Manipulation

Cited by 142 publications

References 27 publications

Constraint Handling in Continuous-Time DDP-Based Model Predictive Control

Constraint Handling in Continuous-Time DDP-Based Model Predictive Control

Passivity-based control for haptic teleoperation of a legged manipulator in presence of time-delays

Bio-Inspired Take-Off Maneuver and Control in Vertical Jumping for Quadruped Robot with Manipulator

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