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Collision-free navigation in cluttered environments with static and dynamic obstacles is essential for many multi-robot tasks. Dynamic obstacles may also be interactive, i.e., their behavior varies based on the behavior of other entities.…

Robotics · Computer Science 2024-05-21 Baskın Şenbaşlar , Gaurav S. Sukhatme

As a core part of autonomous driving systems, motion planning has received extensive attention from academia and industry. However, real-time trajectory planning capable of spatial-temporal joint optimization is challenged by nonholonomic…

Robotics · Computer Science 2023-04-11 Zhichao Han , Yuwei Wu , Tong Li , Lu Zhang , Liuao Pei , Long Xu , Chengyang Li , Changjia Ma , Chao Xu , Shaojie Shen , Fei Gao

In robotics, contemporary strategies are learning-based, characterized by a complex black-box nature and a lack of interpretability, which may pose challenges in ensuring stability and safety. To address these issues, we propose integrating…

Robotics · Computer Science 2024-08-23 Mehdi Heydari Shahna , Seyed Adel Alizadeh Kolagar , Jouni Mattila

We present an algorithm, based on the Differential Dynamic Programming framework, to handle trajectory optimization problems in which the horizon is determined online rather than fixed a priori. This algorithm exhibits exact one-step…

Robotics · Computer Science 2021-11-18 Kyle Stachowicz , Evangelos A. Theodorou

In this paper, we present a novel approach to efficiently generate collision-free optimal trajectories for multiple non-holonomic mobile robots in obstacle-rich environments. Our approach first employs a graph-based multi-agent path planner…

Robotics · Computer Science 2021-01-29 Juncheng Li , Maopeng Ran , Lihua Xie

Risk-aware navigation in unknown environments is a fundamental challenge for autonomous vehicles operating in complex urban systems. To address this issue, this paper presents a differentiable optimization layered safety-critical control…

Systems and Control · Electrical Eng. & Systems 2026-05-19 Jinyang Dong , Shizhen Wu , Yongchun Fang

Optimal trajectory design is computationally expensive for nonlinear and high-dimensional dynamical systems. The challenge arises from the non-convex nature of the optimization problem with multiple local optima, which usually requires a…

Robotics · Computer Science 2024-10-07 Anjian Li , Zihan Ding , Adji Bousso Dieng , Ryne Beeson

Autonomous navigation requires robots to generate trajectories for collision avoidance efficiently. Although plenty of previous works have proven successful in generating smooth and spatially collision-free trajectories, their solutions…

Robotics · Computer Science 2023-09-18 Zhefan Xu , Kenji Shimada

Collision detection is a core component of robotics applications such as simulation, control, and planning. Traditional algorithms like GJK+EPA compute witness points (i.e., the closest or deepest-penetration pairs between two objects) but…

Robotics · Computer Science 2026-03-03 Jiayi Chen , Wei Zhao , Liangwang Ruan , Baoquan Chen , He Wang

Efficient trajectory planning for urban intersections is currently one of the most challenging tasks for an Autonomous Vehicle (AV). Courteous behavior towards other traffic participants, the AV's comfort and its progression in the…

Robotics · Computer Science 2020-10-08 Oliver Speidel , Maximilian Graf , Ankit Kaushik , Thanh Phan-Huu , Andreas Wedel , Klaus Dietmayer

Collision detection appears as a canonical operation in a large range of robotics applications from robot control to simulation, including motion planning and estimation. While the seminal works on the topic date back to the 80s, it is only…

Connected and automated vehicles provide a new opportunity for highly advanced collision avoidance, in which several cars cooperate to reach an optimal overall outcome, that no single car acting in isolation could achieve. For example, one…

Systems and Control · Computer Science 2019-04-16 Charles Wartnaby , Daniele Bellan

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

An emerging class of trajectory optimization methods enforces collision avoidance by jointly optimizing the robot's configuration and a separating hyperplane. However, as linear separators only apply to convex sets, these methods require…

Robotics · Computer Science 2026-01-15 Shuoye Li , Zhiyuan Song , Yulin Li , Zhihai Bi , Jun Ma

We present a fully distributed collision avoidance algorithm based on convex optimization for a team of mobile robots. This method addresses the practical case in which agents sense each other via measurements from noisy on-board sensors…

Optimization and Control · Mathematics 2019-06-04 Guillermo Angeris , Kunal Shah , Mac Schwager

Mobile robots in dynamic environments require fast planning, especially when onboard computational resources are limited. While classic potential field based algorithms may suffice in simple scenarios, in most cases algorithms able to…

Robotics · Computer Science 2023-12-06 Fabio DallaLibera , Shinya Abe , Takeshi Ando

The imminent integration of autonomous vehicles and mobile robots in urban settings presents a critical safety challenge for future intelligent transportation systems. This paper addresses the complex problem of coordinating heterogeneous…

Multiagent Systems · Computer Science 2026-05-28 Wenzhe Song , Hao Zhang

Uncertain dynamic obstacles, such as pedestrians or vehicles, pose a major challenge for optimal robot navigation with safety guarantees. Previous work on motion planning has followed two main strategies to provide a safe bound on an…

Collision-free mobile robot navigation is an important problem for many robotics applications, especially in cluttered environments. In such environments, obstacles can be static or dynamic. Dynamic obstacles can additionally be…

Robotics · Computer Science 2023-02-28 Baskın Şenbaşlar , Gaurav S. Sukhatme

A computational revolution unleashed the power of artificial neural networks. At the heart of that revolution is automatic differentiation, which calculates the derivative of a performance measure relative to a large number of parameters.…

Quantitative Methods · Quantitative Biology 2023-12-27 Steven A. Frank