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We propose MIMOC: Motion Imitation from Model-Based Optimal Control. MIMOC is a Reinforcement Learning (RL) controller that learns agile locomotion by imitating reference trajectories from model-based optimal control. MIMOC mitigates…

Robotics · Computer Science 2023-05-19 AJ Miller , Shamel Fahmi , Matthew Chignoli , Sangbae Kim

Legged locomotion is a complex control problem that requires both accuracy and robustness to cope with real-world challenges. Legged systems have traditionally been controlled using trajectory optimization with inverse dynamics. Such…

Robotics · Computer Science 2024-01-23 Fabian Jenelten , Junzhe He , Farbod Farshidian , Marco Hutter

Control policy learning for modular robot locomotion has previously been limited to proprioceptive feedback and flat terrain. This paper develops policies for modular systems with vision traversing more challenging environments. These…

Robotics · Computer Science 2023-05-02 Julian Whitman , Howie Choset

Task space trajectory tracking for quadruped robots plays a crucial role on achieving dexterous maneuvers in unstructured environments. To fulfill the control objective, the robot should apply forces through the contact of the legs with the…

Off-road navigation on vertically challenging terrain, involving steep slopes and rugged boulders, presents significant challenges for wheeled robots both at the planning level to achieve smooth collision-free trajectories and at the…

Robotics · Computer Science 2024-10-29 Tong Xu , Chenhui Pan , Xuesu Xiao

The robustness of legged locomotion is crucial for quadrupedal robots in challenging terrains. Recently, Reinforcement Learning (RL) has shown promising results in legged locomotion and various methods try to integrate privileged…

Robotics · Computer Science 2023-09-04 Jiyuan Shi , Chenjia Bai , Haoran He , Lei Han , Dong Wang , Bin Zhao , Mingguo Zhao , Xiu Li , Xuelong Li

Payload transport over flat terrain via multi-wheel robot carriers is well-understood, highly effective, and configurable. In this paper, our goal is to provide similar effectiveness and configurability for transport over rough terrain that…

High-fidelity simulation is essential for robotics research, enabling safe and efficient testing of perception, control, and navigation algorithms. However, achieving both photorealistic rendering and accurate physics modeling remains a…

Robotics · Computer Science 2026-04-08 Jonathan Embley-Riches , Jianwei Liu , Simon Julier , Dimitrios Kanoulas

Wheeled bipedal robots have garnered increasing attention in exploration and inspection. However, most research simplifies calculations by ignoring leg dynamics, thereby restricting the robot's full motion potential. Additionally, robots…

Robotics · Computer Science 2025-11-11 Cong Wen , Yunfei Li , Kexin Liu , Yixin Qiu , Xuanhong Liao , Tianyu Wang , Dingchuan Liu , Tao Zhang , Ximin Lyu

In this paper, we propose a robust controller that achieves natural and stably fast locomotion on a real blind quadruped robot. With only proprioceptive information, the quadruped robot can move at a maximum speed of 10 times its body…

Robotics · Computer Science 2022-07-05 Xu Chang , Zhitong Zhang , Honglei An , Hongxu Ma , Qing Wei

In this paper, we describe an approach to achieve dynamic legged locomotion on physical robots which combines existing methods for control with reinforcement learning. Specifically, our goal is a control hierarchy in which highest-level…

Robotics · Computer Science 2021-03-15 Kevin Green , Yesh Godse , Jeremy Dao , Ross L. Hatton , Alan Fern , Jonathan Hurst

We present a novel control strategy for dynamic legged locomotion in complex scenarios, that considers information about the morphology of the terrain in contexts when only on-board mapping and computation are available. The strategy is…

Multi-legged robots with six or more legs are not in common use, despite designs with superior stability, maneuverability, and a low number of actuators being available for over 20 years. This may be in part due to the difficulty in…

Robotics · Computer Science 2024-01-05 Ziyou Wu , Dan Zhao , Shai Revzen

Most autonomous navigation systems assume wheeled robots are rigid bodies and their 2D planar workspaces can be divided into free spaces and obstacles. However, recent wheeled mobility research, showing that wheeled platforms have the…

Robotics · Computer Science 2023-09-26 Aniket Datar , Chenhui Pan , Xuesu Xiao

Multi-legged elongate robots hold promise for maneuvering through complex environments. Prior work has demonstrated that reliable locomotion can be achieved using open-loop body undulation and foot placement on rugose terrain. However,…

In the context of legged robots, adaptive behavior involves adaptive balancing and adaptive swing foot reflection. While adaptive balancing counteracts perturbations to the robot, adaptive swing foot reflection helps the robot to navigate…

Robotics · Computer Science 2024-03-21 Yiyu Chen , Quan Nguyen

Planetary exploration missions require robots capable of navigating extreme and unknown environments. While wheeled rovers have dominated past missions, their mobility is limited to traversable surfaces. Legged robots, especially…

A deformable land-air robot is introduced with excellent driving and flying capabilities, offering a smooth switching mechanism between the two modes. An elaborate coupled dynamics model is established for the robot, including rotors,…

Robotics · Computer Science 2022-12-05 Xinyu Zhang , Yuanhao Huang , Kangyao Huang , Ziqi Zhao , Jingwei Li , Huaping Liu , Jun Li

Adaptive morphogenetic robots adapt their morphology and control policies to meet changing tasks and environmental conditions. Many such systems leverage soft components, which enable shape morphing but also introduce simulation and control…

Neglecting complex aerodynamic effects hinders high-speed yet high-precision multirotor autonomy. In this paper, we present a computationally efficient learning-based model predictive controller that simultaneously optimizes a trajectory…

Robotics · Computer Science 2024-02-19 Babak Akbari , Melissa Greeff