In this paper, we introduce the concept of using passive arm structures with intrinsic impedance for robot-robot and human-robot collaborative carrying with quadruped robots. The concept is meant for a leader-follower task and takes a minimalist approach that focuses on exploiting the robots' payload capabilities and reducing energy consumption, without compromising the robot locomotion capabilities. We introduce a preliminary arm mechanical design and describe how to use its joint displacements to guide the robot's motion. To control the robot's locomotion, we propose a decentralized Model Predictive Controller that incorporates an approximation of the arm dynamics and the estimation of the external forces from the collaborative carrying. We validate the overall system experimentally by performing both robot-robot and human-robot collaborative carrying on a stair-like obstacle and on rough terrain.
Italian Institute of Technology（意大利技术研究院）；University of Genoa（热那亚大学）
This paper presents a simplified model-based trajectory optimization (TO) formulation for motion planning on quadruped mobile manipulators that carry heavy payload of known mass. The proposed payload-aware formulation simultaneously plans locomotion, payload manipulation and considers both robot and payload model dynamics while remaining computationally efficient. At the presence of heavy payload, the approach exhibits reduced leg outstretching (thus increased manipulability) in kinematically demanding motions due to the contribution of payload manipulation in the optimization. The framework's…
Physics-informed Neural Network Predictive Control for Quadruped Locomotion
School of Intelligent Systems Engineering, Shenzhen Campus of Sun Yat-sen University（中山大学深圳校区智能系统工程学院）；General Embodied AI Center of Sun Yat-sen University（中山大学通用具身人工智能中心）；Guangdong Provincial Key Laboratory of Fire Science and Intelligent Emergency Technology（广东省火灾科学与智能应急技术重点实验室）；College of Engineering, Peking University（北京大学工学院）；Robotics and Autonomous Systems Thrust, The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州）机器人与自主系统部）；George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology（佐治亚理工学院乔治·W. 伍德拉夫机械工程学院）
Adaptive Model-Base Control of Quadrupeds via Online System Identification using Kalman Filter
Robotics Innovation Center, German Research Center for Artificial Intelligence (DFKI GmbH)（机器人创新中心，德国人工智能研究中心（DFKI GmbH））；AG Robotik, University of Bremen（机器人技术研究所，不莱梅大学）；Dynamics Division, Department of Mechanics & Maritime Sciences, Chalmers University of Technology（动力学研究所，机械与海洋科学系，查尔姆斯理工大学）
Robust Nonprehensile Object Transport with Quadruped Robots
Technical University of Munich (TUM)（慕尼黑工业大学）；Tampere University（坦佩雷大学）；University of Naples Federico II（那不勒斯费德里科二世大学）；Mohamed Bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）
The quadruped robot is a versatile mobile platform with potential ability for high payload carrying. However, most of the existing quadruped robots aim at high maneuverability, highly dynamic and agile locomotion. In spite of this, payload carrying is still an indispensable ability for the quadruped robots. Design of a quadruped robot with high payload capacity is yet deeply explored. In this study, a 50 kg electrically-actuated quadruped robot, Kirin, is presented to leverage the payload carrying capability. Kirin is an characterized with prismatic quasi-direct-drive (QDD) leg. This mechanism…
Modern robotic systems are endowed with superior mobility and mechanical skills that make them suited to be employed in real-world scenarios, where interactions with heavy objects and precise manipulation capabilities are required. For instance, legged robots with high payload capacity can be used in disaster scenarios to remove dangerous material or carry injured people. It is thus essential to develop planning algorithms that can enable complex robots to perform motion and manipulation tasks accurately. In addition, online adaptation mechanisms with respect to new, unknown environments are n…
Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS)（深圳人工智能与机器人研究院）；Georgia Institute of Technology（佐治亚理工学院）；Hong Kong University of Science and Technology（香港科技大学）；Southern University of Science and Technology (SUSTech)（南方科技大学）；Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））
Quadruped robots manifest great potential to traverse rough terrains with payload. Numerous traditional control methods for legged dynamic locomotion are model-based and exhibit high sensitivity to model uncertainties and payload variations. Therefore, high-performance model parameter estimation becomes indispensable. However, the inertia parameters of payload are usually unknown and dynamically changing when the quadruped robot is deployed in versatile tasks. To address this problem, online identification of the inertia parameters and the Center of Mass (CoM) position of the payload for the q…
Virginia Tech（弗吉尼亚理工大学）；California Institute of Technology（加州理工学院）
This paper presents a layered control approach for real-time trajectory planning and control of robust cooperative locomotion by two holonomically constrained quadrupedal robots. A novel interconnected network of reduced-order models, based on the single rigid body (SRB) dynamics, is developed for trajectory planning purposes. At the higher level of the control architecture, two different model predictive control (MPC) algorithms are proposed to address the optimal control problem of the interconnected SRB dynamics: centralized and distributed MPCs. The distributed MPC assumes two local quadra…
A Nonlinear MPC Framework for Loco-Manipulation of Quadrupedal Robots with Non-Negligible Manipulator Dynamics
Department of Mechanical Engineering, Virginia Tech（弗吉尼亚理工大学机械工程系）；California Institute of Technology（加州理工学院）；School of Neuroscience, Virginia Tech（弗吉尼亚理工大学神经科学学院）
Adaptive Legged Locomotion via Online Learning for Model Predictive Control
Department of Aerospace Engineering, University of Michigan（密歇根大学航空航天工程系）；Institute for Robotics and Intelligent Machines, Georgia Institute of Technology（佐治亚理工学院机器人与智能机器研究所）
University of California, Los Angeles（加利福尼亚大学洛杉矶分校）
This paper introduces SCALER, a quadrupedal robot that demonstrates climbing on bouldering walls, overhangs, ceilings and trotting on the ground. SCALER is one of the first high-degrees of freedom four-limbed robots that can free-climb under the Earth's gravity and one of the most mechanically efficient quadrupeds on the ground. Where other state-of-the-art climbers specialize in climbing, SCALER promises practical free-climbing with payload \textit{and} ground locomotion, which realizes true versatile mobility. A new climbing gait, SKATE gait, increases the payload by utilizing the SCALER bod…
Virginia Tech（弗吉尼亚理工大学）；California Institute of Technology（加州理工学院）
The aim of this work is to define a planner that enables robust legged locomotion for complex multi-agent systems consisting of several holonomically constrained quadrupeds. To this end, we employ a methodology based on behavioral systems theory to model the sophisticated and high-dimensional structure induced by the holonomic constraints. The resulting model is then used in tandem with distributed control techniques such that the computational burden is shared across agents while the coupling between agents is preserved. Finally, this distributed model is framed in the context of a predictive…
School of Informatics, University of Edinburgh（爱丁堡大学信息学院）；Oxford Robotics Institute, University of Oxford（牛津大学牛津机器人研究所）
This paper focuses on robustness to disturbance forces and uncertain payloads. We present a novel formulation to optimize the robustness of dynamic trajectories. A straightforward transcription of this formulation into a nonlinear programming problem is not tractable for state-of-the-art solvers, but it is possible to overcome this complication by exploiting the structure induced by the kinematics of the robot. The non-trivial transcription proposed allows trajectory optimization frameworks to converge to highly robust dynamic solutions. We demonstrate the results of our approach using a quadr…
Symmetry-Guided Memory Augmentation for Efficient Locomotion Learning
Department of Mechanical and Process Engineering, ETH Zurich, Switzerland（瑞士苏黎世联邦理工学院机械与过程工程系）；ETH AI Center, ETH Zurich, Switzerland（瑞士苏黎世联邦理工学院人工智能中心）；Department of Computer Science, ETH Zurich, Switzerland（瑞士苏黎世联邦理工学院计算机科学系）
United States Military Academy（美国军事学院）；Massachusetts Institute of Technology（麻省理工学院）
The Extra Robotic Legs (XRL) system is a robotic augmentation worn by a human operator consisting of two articulated robot legs that walk with the operator and help bear a heavy backpack payload. It is desirable for the Human-XRL quadruped system to walk with the rear legs lead the front by 25% of the gait period, minimizing the energy lost from foot impacts while maximizing balance stability. Unlike quadrupedal robots, the XRL cannot command the human's limbs to coordinate quadrupedal locomotion. Using a pair of Rimless Wheel models, it is shown that the systems coupled with a spring and damp…
Safe Control of Quadruped in Varying Dynamics via Safety Index Adaptation
Mechanical Engineering Department, Carnegie Mellon University（卡内基梅隆大学机械工程系）；Robotics Institute, Carnegie Mellon University（卡内基梅隆大学机器人研究所）；Mechanical Engineering Department, New Mexico Institute of Mining and Technology（新墨西哥州矿业与技术研究所机械工程系）
Dual-Quadruped Collaborative Transportation in Narrow Environments via Safe Reinforcement Learning
The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；Advanced Remanufacturing & Technology Centre (ARTC)（先进再制造与技术中心）；Agency for Science, Technology and Research (A*STAR)（科技研究局）；Cheng Kar-Shun Robotics Institute, The Hong Kong University of Science and Technology（陈克舜机器人研究所，香港科技大学）
LiMo-Calib: On-Site Fast LiDAR-Motor Calibration for Quadruped Robot-Based Panoramic 3D Sensing System
China-Singapore International Joint Research Institute (CSIJRI)（中新国际联合研究院）；School of Electrical and Electronic Engineering, Nanyang Technological University（南洋理工大学电气与电子工程学院）
Sensor Configuration Matters: A Systematic Evaluation of Multimodal SLAM on Quadruped Robots
Machine Intelligence and Robotics Lab, Karlsruhe Institute of Technology (KIT)（卡尔斯鲁厄理工学院智能机器人实验室）；Institute for Intelligent Systems, Esslingen University of Applied Sciences（埃森堡应用科学大学智能系统研究所）；Department of Computer Science, University of Freiburg（弗赖堡大学计算机科学系）
A Three-Level Whole-Body Disturbance Rejection Control Framework for Dynamic Motions in Legged Robots
School of Artificial Intelligence and Automation, Huazhong University of Science and Technology（人工智能与自动化学院，华中科技大学）；State Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology（智能制造装备与技术国家重点实验室，华中科技大学）
A Robotic Testing Platform for Pipelined Discovery of Resilient Soft Actuators
Department of Mechanical and Industrial Engineering, University of Toronto（多伦多大学机械与工业工程系）；Institute of Materials Science, University of Connecticut（康涅狄格大学材料科学研究所）；School of Mechanical, Aerospace, and Manufacturing Engineering, University of Connecticut（康涅狄格大学机械、航空航天与制造工程学院）；Material Science and Engineering, University of Connecticut（康涅狄格大学材料科学与工程系）；Inorganic Polymers Department, Petru Poni Institute of Macromolecular Chemistry（彼得·波尼宏分子化学研究所无机聚合物部门）
