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We present a versatile nonlinear model predictive control (NMPC) formulation for quadrupedal locomotion. Our formulation jointly optimizes a base trajectory and a set of footholds over a finite time horizon based on simplified dynamics…

机器人学 · 计算机科学 2022-07-22 Dongho Kang , Flavio De Vincenti , Stelian Coros

Re-planning in legged locomotion is crucial to track the desired user velocity while adapting to the terrain and rejecting external disturbances. In this work, we propose and test in experiments a real-time Nonlinear Model Predictive…

This paper proposes a novel control framework for agile and robust bipedal locomotion, addressing model discrepancies between full-body and reduced-order models. Specifically, assumptions such as constant centroidal inertia have introduced…

机器人学 · 计算机科学 2024-09-17 Seung Hyeon Bang , Jaemin Lee , Carlos Gonzalez , Luis Sentis

The complex tasks such as surveillance, construction, search and rescue can benefit of the maneuverability of multirotor Micro Aerial Vehicles (MAVs) to obtain robust, cooperative system behavior and formation control is a prominent…

系统与控制 · 计算机科学 2019-04-09 I. Kagan Erunsal , Rodrigo Ventura , Alcherio Martinoli

Human beings can utilize multiple balance strategies, e.g. step location adjustment and angular momentum adaptation, to maintain balance when walking under dynamic disturbances. In this work, we propose a novel Nonlinear Model Predictive…

机器人学 · 计算机科学 2025-03-21 Jiatao Ding , Chengxu Zhou , Songyan Xin , Xiaohui Xiao , Nikos Tsagarakis

Model predictive control (MPC) combined with reduced-order template models has emerged as a powerful tool for trajectory optimization in dynamic legged locomotion. However, loco-manipulation tasks performed by legged robots introduce…

In this paper, we propose, discuss, and validate an online Nonlinear Model Predictive Control (NMPC) method for multi-rotor aerial systems with arbitrarily positioned and oriented rotors which simultaneously addresses the local reference…

机器人学 · 计算机科学 2020-09-11 Davide Bicego , Jacopo Mazzetto , Ruggero Carli , Marcello Farina , Antonio Franchi

This paper presents a stochastic/robust nonlinear model predictive control (NMPC) to enhance the robustness of model-based legged locomotion against contact uncertainties. We integrate the contact uncertainties into the covariance…

机器人学 · 计算机科学 2024-09-16 Sotaro Katayama , Noriaki Takasugi , Mitsuhisa Kaneko , Norio Nagatsuka , and Masaya Kinoshita

The use of exoskeleton robots is increasing due to the rising number of musculoskeletal injuries. However, their effectiveness depends heavily on the design of control systems. Designing robust controllers is challenging because of…

机器人学 · 计算机科学 2025-09-29 Alireza Aliyari , Gholamreza Vossoughi

Thanks to recent advancements in accelerating non-linear model predictive control (NMPC), it is now feasible to deploy whole-body NMPC at real-time rates for humanoid robots. However, enforcing inequality constraints in real time for such…

机器人学 · 计算机科学 2024-10-23 Charles Khazoom , Seungwoo Hong , Matthew Chignoli , Elijah Stanger-Jones , Sangbae Kim

This thesis presents a unified control framework for agile and fault-tolerant flight of the Multi-Modal Mobility Morphobot (M4) in aerial mode. The M4 robot is capable of transitioning between ground and aerial locomotion. The articulated…

机器人学 · 计算机科学 2025-04-30 Shashwat Pandya

Non-linear model predictive control (nMPC) is a powerful approach to control complex robots (such as humanoids, quadrupeds, or unmanned aerial manipulators (UAMs)) as it brings important advantages over other existing techniques. The…

机器人学 · 计算机科学 2023-07-28 Josep Martí-Saumell , Joan Solà , Angel Santamaria-Navarro , Juan Andrade-Cetto

Heavy-duty hydraulic manipulators (HHMs) operate under strict physical and safety-critical constraints due to their large size, high power, and complex nonlinear dynamics. Ensuring that both joint-level and end-effector trajectories remain…

机器人学 · 计算机科学 2025-10-28 Alvaro Paz , Mahdi Hejrati , Pauli Mustalahti , Jouni Mattila

Ensuring safe and effective collaboration between humans and autonomous legged robots is a fundamental challenge in shared autonomy, particularly for teleoperated systems navigating cluttered environments. Conventional shared-control…

Tendon-Driven Continuum Robots (TDCRs) have the potential to be used in minimally invasive surgery and industrial inspection, where the robot must enter narrow and confined spaces. We propose a Model Predictive Control (MPC) approach to…

机器人学 · 计算机科学 2024-09-17 Maximillian Hachen , Chengnan Shentu , Sven Lilge , Jessica Burgner-Kahrs

Designing a model predictive control (MPC) scheme that enables a mobile robot to safely navigate through an obstacle-filled environment is a complicated yet essential task in robotics. In this technical report, safety refers to ensuring…

机器人学 · 计算机科学 2025-08-12 Dennis Benders , Laura Ferranti , Johannes Köhler

This paper presents a new flight control framework for tilt-rotor multirotor uncrewed aerial vehicles (MRUAVs). Tiltrotor designs offer full actuation but introduce complexity in control allocation due to actuator redundancy. We propose a…

机器人学 · 计算机科学 2024-06-25 Zeinab Shayan , Jann Cristobal , Mohammadreza Izadi , Amin Yazdanshenas , Mehdi Naderi , Reza Faieghi

Flexible robots may overcome some of the industry's major challenges, such as enabling intrinsically safe human-robot collaboration and achieving a higher payload-to-mass ratio. However, controlling flexible robots is complicated due to…

Dynamic legged locomotion is a challenging topic because of the lack of established control schemes which can handle aerial phases, short stance times, and high-speed leg swings. In this paper, we propose a controller combining whole-body…

机器人学 · 计算机科学 2019-09-17 Donghyun Kim , Jared Di Carlo , Benjamin Katz , Gerardo Bledt , Sangbae Kim

This paper proposes a Nonlinear Model-Predictive Control (NMPC) method capable of finding and converging to energy-efficient regular oscillations, which require no control action to be sustained. The approach builds up on the recently…

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