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Generating safe behaviors for autonomous systems is important as they continue to be deployed in the real world, especially around people. In this work, we focus on developing a novel safe controller for systems where there are multiple…

机器人学 · 计算机科学 2024-07-03 Ravi Pandya , Tianhao Wei , Changliu Liu

Human-robot interactions have been recognized to be a key element of future industrial collaborative robots (co-robots). Unlike traditional robots that work in structured and deterministic environments, co-robots need to operate in highly…

机器人学 · 计算机科学 2018-08-14 Changliu Liu , Masayoshi Tomizuka

It is critical to ensure safety for humanoid robots in real-world applications without compromising performance. In this paper, we consider the problem of dexterous safety, featuring limb-level geometry constraints for avoiding both…

机器人学 · 计算机科学 2025-02-06 Rui Chen , Yifan Sun , Changliu Liu

Safety in terms of collision avoidance for multi-robot systems is a difficult challenge under uncertainty, non-determinism and lack of complete information. This paper aims to propose a collision avoidance method that accounts for both…

机器人学 · 计算机科学 2020-12-09 Wenhao Luo , Wen Sun , Ashish Kapoor

In this paper we present a framework that allows the motion control of a robotic arm automatically handling different kinds of safety-related tasks. The developed controller is based on a Task-Priority Inverse Kinematics algorithm that…

机器人学 · 计算机科学 2019-05-30 Paolo Di Lillo , Filippo Arrichiello , Gianluca Antonelli , Stefano Chiaverini

Safe and efficient collaboration among multiple robots in unstructured environments is increasingly critical in the era of Industry 4.0. However, achieving robust and autonomous collaboration among humans and other robots requires modern…

机器人学 · 计算机科学 2023-03-29 Apan Dastider , Mingjie Lin

Human-robot collaborations have been recognized as an essential component for future factories. It remains challenging to properly design the behavior of those co-robots. Those robots operate in dynamic uncertain environment with limited…

机器人学 · 计算机科学 2018-09-24 Changliu Liu , Te Tang , Hsien-Chung Lin , Yujiao Cheng , Masayoshi Tomizuka

The successful implementation of Physical Human-Robot Interaction in industrial environments depends on ensuring safe collaboration between human operators and robotic devices. This necessitates the adoption of measures that guarantee the…

机器人学 · 计算机科学 2024-09-04 Armin Ghanbarzadeh , Esmaeil Najafi

Human safety has always been the main priority when working near an industrial robot. With the rise of Human-Robot Collaborative environments, physical barriers to avoiding collisions have been disappearing, increasing the risk of accidents…

Nonlinear controllers for floating base systems in contact with the environment are often framed as quadratic programming (QP) optimization problems. Common drawbacks of such QP based controllers are: the control input often experiences…

机器人学 · 计算机科学 2020-09-09 Ahmad Gazar , Gabriele Nava , Francisco Javier Andrade Chavez , Daniele Pucci

This paper presents an approach to deal with safety of dynamical systems in presence of multiple non-convex unsafe sets. While optimal control and model predictive control strategies can be employed in these scenarios, they suffer from high…

系统与控制 · 电气工程与系统科学 2021-06-14 Gennaro Notomista , Matteo Saveriano

Ensuring safety for human-interactive robotics is important due to the potential for human injury. The key challenge is defining safety in a way that accounts for the complex range of human behaviors without modeling the human as an…

机器人学 · 计算机科学 2021-10-12 Jeevana Priya Inala , Yecheng Jason Ma , Osbert Bastani , Xin Zhang , Armando Solar-Lezama

Passivity is necessary for robots to fluidly collaborate and interact with humans physically. Nevertheless, due to the unconstrained nature of passivity-based impedance control laws, the robot is vulnerable to infeasible and unsafe…

机器人学 · 计算机科学 2024-03-18 Zhiquan Zhang , Tianyu Li , Nadia Figueroa

Deep reinforcement learning (DRL) is emerging as a promising method for adaptive robotic motion and complex task automation, effectively addressing the limitations of traditional control methods. However, ensuring safety throughout both the…

系统与控制 · 电气工程与系统科学 2025-10-30 Seyed Adel Alizadeh Kolagar , Mehdi Heydari Shahna , Jouni Mattila

Soft robots are notoriously hard to control. This is partly due to the scarcity of models able to capture their complex continuum mechanics, resulting in a lack of control methodologies that take full advantage of body compliance. Currently…

机器人学 · 计算机科学 2020-09-18 Noel Naughton , Jiarui Sun , Arman Tekinalp , Girish Chowdhary , Mattia Gazzola

Robots built from soft materials will inherently apply lower environmental forces than their rigid counterparts, and therefore may be more suitable in sensitive settings with unintended contact. However, these robots' applied forces result…

In this paper, we propose and validate a Joint-Initiative Supervised Autonomy (JISA) framework for Human-Robot Interaction (HRI), in which a robot maintains a measure of its self-confidence (SC) while performing a task, and only prompts the…

机器人学 · 计算机科学 2021-09-13 Abbas Sidaoui , Naseem Daher , Daniel Asmar

Multi-robot systems are increasingly being used for critical applications such as rescuing injured people, delivering food and medicines, and monitoring key areas. These applications usually involve navigating at high speeds through…

机器人学 · 计算机科学 2025-11-19 Jaskirat Singh , Rohan Chandra

This paper aims to provide a clear and rigorous understanding of commonly recognized safety constraints in physical human-robot interaction, particularly regarding ISO/TS 15066. We investigate the derivation of these constraints, critically…

系统与控制 · 电气工程与系统科学 2026-04-03 Riccardo Zanella , Federico Califano , Stefano Stramigioli

Conventional passivity-based torque controllers for manipulators are typically unconstrained, which can lead to safety violations under external perturbations. In this paper, we employ viability theory to pre-compute safe sets in the…

系统与控制 · 电气工程与系统科学 2026-03-24 Zizhe Zhang , Yicong Wang , Zhiquan Zhang , Tianyu Li , Nadia Figueroa
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