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Motion planning trajectories for a multi-limbed robot to climb up walls requires a unique combination of constraints on torque, contact force, and posture. This paper focuses on motion planning for one particular setup wherein a six-legged…

Robotics · Computer Science 2023-08-16 Xuan Lin , Jingwen Zhang , Junjie Shen , Gabriel Fernandez , Dennis W Hong

Contact-based motion planning for manipulation, object exploration or balancing often requires finding sequences of fixed and sliding contacts and planning the transition from one contact in the environment to another. However, most…

Robotics · Computer Science 2021-03-18 Marie-Therese Khoury , Andreas Orthey , Marc Toussaint

Many-legged elongated robots show promise for reliable mobility on rugged landscapes. However, most studies on these systems focus on planar motion planning without addressing rapid vertical motion. Despite their success on mild rugged…

Robotics · Computer Science 2025-04-22 Juntao He , Baxi Chong , Massimiliano Iaschi , Vincent R. Nienhusser , Sehoon Ha , Daniel I. Goldman

Motion planning for a multi-limbed climbing robot must consider the robot's posture, joint torques, and how it uses contact forces to interact with its environment. This paper focuses on motion planning for a robot that uses nontraditional…

Traditional motion planning approaches for multi-legged locomotion divide the problem into several stages, such as contact search and trajectory generation. However, reasoning about contacts and motions simultaneously is crucial for the…

While motion planning of locomotion for legged robots has shown great success, motion planning for legged robots with dexterous multi-finger grasping is not mature yet. We present an efficient motion planning framework for simultaneously…

Robotics · Computer Science 2023-01-18 Yuki Shirai , Xuan Lin , Alexander Schperberg , Yusuke Tanaka , Hayato Kato , Varit Vichathorn , Dennis Hong

Humanoid robots rely on multi-contact planners to navigate a diverse set of environments, including those that are unstructured and highly constrained. To synthesize stable multi-contact plans within a reasonable time frame, most planners…

Robotics · Computer Science 2024-10-14 Carlos Gonzalez , Luis Sentis

We study the problem of motion-planning for free-flying multi-link robots and develop a sampling-based algorithm that is specifically tailored for the task. Our work is based on the simple observation that the set of configurations for…

Robotics · Computer Science 2015-11-26 Oren Salzman , Kiril Solovey , Dan Halperin

As robots move from the laboratory into the real world, motion planning will need to account for model uncertainty and risk. For robot motions involving intermittent contact, planning for uncertainty in contact is especially important, as…

Robotics · Computer Science 2021-10-01 Luke Drnach , John Z. Zhang , Ye Zhao

Contact planning is crucial in locomoting systems.Specifically, appropriate contact planning can enable versatile behaviors (e.g., sidewinding in limbless locomotors) and facilitate speed-dependent gait transitions (e.g., walk-trot-gallop…

We present a novel receding-horizon multi-contact motion planner for legged robots in challenging scenarios, able to plan motions such as chimney climbing, navigating very narrow passages or crossing large gaps. Our approach adds new…

Robotics · Computer Science 2026-02-12 Daniel S. J. Derwent , Simon Watson , Bruno V. Adorno

Environments with large terrain height variations present great challenges for legged robot locomotion. Drawing inspiration from fire ants' collective assembly behavior, we study strategies that can enable two ``connectable'' robots to…

Robotics · Computer Science 2025-02-04 Haodi Hu , Xingjue Liao , Wuhao Du , Feifei Qian

Legged robots leverage ground contacts and the reaction forces they provide to achieve agile locomotion. However, uncertainty coupled with contact discontinuities can lead to failure, especially in real-world environments with unexpected…

Robotics · Computer Science 2023-09-11 Yanhao Yang , Joseph Norby , Justin K. Yim , Aaron M. Johnson

In this paper, we present a task space-based local motion planner that incorporates collision avoidance and constraints on end-effector motion during the execution of a task. Our key technical contribution is the development of a novel…

Robotics · Computer Science 2021-04-19 Anirban Sinha , Anik Sarker , Nilanjan Chakraborty

Advances in planetary robotics have led to wheeled robots that have beamed back invaluable science data from the surface of the Moon and Mars. However, these large wheeled robots are unable to access rugged environments such as cliffs,…

Robotics · Computer Science 2018-03-18 Steven Morad , Himangshu Kalita , Jekan Thangavelautham

In this paper, we present an approach for generating a variety of whole-body motions for a humanoid robot. We extend the available Model Predictive Control (MPC) approaches for walking on flat terrain to plan for both vertical motion of the…

This paper is about generating motion plans for high degree-of-freedom systems that account for collisions along the entire body. A particular class of mathematical programs with complementarity constraints become useful in this regard.…

Complex motions for robots are frequently generated by switching among a collection of individual movement primitives. We use this approach to formulate robot motion plans as sequences of primitives to be executed one after the other. When…

Robotics · Computer Science 2018-10-02 Sushant Veer , Ioannis Poulakakis

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

Locomotion for legged robots poses considerable challenges when confronted by obstacles and adverse environments. Footstep planners are typically only designed for one mode of locomotion, but traversing unfavorable environments may require…

Robotics · Computer Science 2016-08-15 Michael X. Grey , Aaron D. Ames , C. Karen Liu
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