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Trajectory planning for mobile robots in cluttered environments remains a major challenge due to narrow passages, where conventional methods often fail or generate suboptimal paths. To address this issue, we propose the adaptive trajectory…

Robotics · Computer Science 2025-10-31 Hahjin Lee , Young J. Kim

Autonomous explorative robots frequently encounter scenarios where multiple future trajectories can be pursued. Often these are cases with multiple paths around an obstacle or trajectory options towards various frontiers. Humans in such…

We present a method for humanoid robot walking on partial footholds such as small stepping stones and rocks with sharp surfaces. Our algorithm does not rely on prior knowledge of the foothold, but information about an expected foothold can…

Despite extensive developments in motion planning of autonomous aerial vehicles (AAVs), existing frameworks faces the challenges of local minima and deadlock in complex dynamic environments, leading to increased collision risks. To address…

Robotics · Computer Science 2026-05-29 Junzhi Li , Teng Long , Jingliang Sun , Jianxin Zhong

As more robots are being deployed into human environments, a human-aware navigation planner needs to handle multiple contexts that occur in indoor and outdoor environments. In this paper, we propose a tunable human-aware robot navigation…

Robotics · Computer Science 2021-06-21 Phani Singamaneni , Anthony Favier , Rachid Alami

Planning over unstructured terrain presents a significant challenge in the field of legged robotics. Although recent works in reinforcement learning have yielded various locomotion strategies, planning over multiple experts remains a…

Hybrid driving-stepping locomotion is an effective approach for navigating in a variety of environments. Long, sufficiently even distances can be quickly covered by driving while obstacles can be overcome by stepping. Our quadruped robot…

Robotics · Computer Science 2018-09-20 Tobias Klamt , Sven Behnke

We present a motion planning algorithm to compute collision-free and smooth trajectories for high-DOF robots interacting with humans in a shared workspace. Our approach uses offline learning of human actions along with temporal coherence to…

Robotics · Computer Science 2017-11-28 Jae Sung Park , Chonhyon Park , Dinesh Manocha

Legged navigation is typically examined within open-world, off-road, and challenging environments. In these scenarios, estimating external disturbances requires a complex synthesis of multi-modal information. This underlines a major…

Robotics · Computer Science 2024-09-30 Junli Ren , Yikai Liu , Yingru Dai , Junfeng Long , Guijin Wang

Planning in environments with moving obstacles remains a significant challenge in robotics. While many works focus on navigation and path planning in obstacle-dense spaces, traversing such congested regions is often avoidable by selecting…

Robotics · Computer Science 2025-06-23 Yaroslav Marchukov , Luis Montano

Bipedal robots have advantages in maneuvering human-centered environments, but face greater failure risk compared to other stable mobile platforms such as wheeled or quadrupedal robots. While learning-based traversability has been widely…

Robotics · Computer Science 2025-12-08 Ziwon Yoon , Lawrence Y. Zhu , Jingxi Lu , Lu Gan , Ye Zhao

Exploration of unknown, unstructured environments, such as in search and rescue, cave exploration, and planetary missions,presents significant challenges due to their unpredictable nature. This unpredictability can lead to inefficient path…

Robotics · Computer Science 2024-10-08 Riana Gagnon Souleiman , Vivek Shankar Varadharajan , Giovanni Beltrame

The problem of navigating a bipedal robot to a desired destination in various environments is very important. However, it is very difficult to solve the navigation problem in real time because the computation time is very long due to the…

Robotics · Computer Science 2022-11-11 Joon-Ha Kim

Navigation and motion control of a robot to a destination are tasks that have historically been performed with the assumption that contact with the environment is harmful. This makes sense for rigid-bodied robots where obstacle collisions…

This paper presents a two-step algorithm for online trajectory planning in indoor environments with unknown obstacles. In the first step, sampling-based path planning techniques such as the optimal Rapidly exploring Random Tree (RRT*)…

Robotics · Computer Science 2023-02-07 Martin Zimmermann , Minh Nhat Vu , Florian Beck , Anh Nguyen , Andreas Kugi

Over the years, the separate fields of motion planning, mapping, and human trajectory prediction have advanced considerably. However, the literature is still sparse in providing practical frameworks that enable mobile manipulators to…

Robotics · Computer Science 2022-07-27 Mark Nicholas Finean , Luka Petrović , Wolfgang Merkt , Ivan Marković , Ioannis Havoutis

This study focuses on a layered, experience-based, multi-modal contact planning framework for agile quadrupedal locomotion over a constrained rebar environment. To this end, our hierarchical planner incorporates locomotion-specific modules…

Robotics · Computer Science 2024-04-16 Max Asselmeier , Jane Ivanova , Ziyi Zhou , Patricio A. Vela , Ye Zhao

Accurate traversability estimation using an online dense terrain map is crucial for safe navigation in challenging environments like construction and disaster areas. However, traversability estimation for legged robots on rough terrains…

In this paper, we present a path planner for low-altitude terrain coverage in known environments with unmanned rotary-wing micro aerial vehicles (MAVs). Airborne systems can assist humanitarian demining by surveying suspected hazardous…

Robotics · Computer Science 2021-12-07 Rik Bähnemann , Nicholas Lawrance , Jen Jen Chung , Michael Pantic , Roland Siegwart , Juan Nieto

Global path planning is the key technology in the design of unmanned surface vehicles. This paper establishes global environment modelling based on electronic charts and hexagonal grids which are proved to be better than square grids in…

Robotics · Computer Science 2018-07-24 Yanlong Wang , Xuemin Yu , Xu Liang
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