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2025 IEEE International Conference on Simulation, Modeling, and Programming for autonomous Robots, SIMPAR 2025

作者： Bacchin, Alberto Marangoni, Fabio Gottardi, Alberto Menegatti, Emanuele University of Padova Intelligent Autonomous System Lab Department of Information Engineering Padua35131 Italy IT+Robotics Srl Vicenza36100 Italy

ISBN: (纸本)9798331516857

The growing volumes of solid waste present a significant challenge for sustainable management. An efficient robotics system for sorting waste materials is essential to improving recycling and contamination removal, but it is often limited by the extreme variation of items to recognize in a cluttered and dirty environment. To bring robots in such scenario, the system must be able to recognize and manipulate different objects, adapting to a high degree of variability. A system based on deep learning can achieve high performance and fulfill these requirements. However, learning models require extensive labeled data, which limits their applicability in this context. Indeed, the complexity of the real-world environment presents a significant challenge to effective data collection, highlighting the importance of data augmentation techniques for creating a suitable dataset for training models for object recognition in this context. To address this challenge, our study investigates the use of Generative Adversarial Networks (GANs) for synthetic data generation in waste-sorting systems. GANs are employed to produce synthetic images of waste streams with corresponding labels that accurately reflect the complexity and diversity of real-world waste. A primary con-cern in synthetic data generation is ensuring alignment between generated images and their labels. To address this, we introduce a novel method for controlling the GAN generation process, which enforces semantic coherence and preserves the intended structure of the labeled data. The experiments demonstrate that semantic segmentation models trained on datasets augmented with these synthetic images perform better in the semantic segmentation of waste. © 2025 IEEE.

关键词： Semantic Segmentation

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Learning to Model Diverse Driving Behaviors in Highly Interactive autonomous Driving Scenarios With Multiagent Reinforcement Learning

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IEEE Systems Journal 2025年第1期19卷 317-326页

作者： Liu, Weiwei Hu, Wenxuan Jing, Wei Lei, Lanxin Gao, Lingping Liu, Yong Zhejiang University The Advanced Perception on Robotics and Intelligent Learning Lab College of Control Science and Engineering Hangzhou310027 China Huzhou Institute of Zhejiang University Zhejiang 310027 China Alibaba DAMO Academy Autonomous Driving Lab Zhejiang 311121 China Huzhou University College of Information Engineering Zhejiang 313000 China

autonomous vehicles trained through multiagent reinforcement learning (MARL) have shown impressive results in many driving scenarios. However, the performance of these trained policies can be impacted when faced with diverse driving styles and personalities, particularly in highly interactive situations. This is because conventional MARL algorithms usually operate under the assumption of fully cooperative behavior among all agents and focus on maximizing team rewards during training. To address this issue, we introduce the personality modeling network (PeMN), which includes a cooperation value function and personality parameters to model the varied interactions in high-interactive scenarios. The PeMN also enables the training of a background traffic flow with diverse behaviors, thereby improving the performance and generalization of the ego vehicle. Our extensive experimental studies, which incorporate different personality parameters in high-interactive driving scenarios, demonstrate that the personality parameters effectively model diverse driving styles and that policies trained with PeMN demonstrate better generalization than traditional MARL methods. © 2007-2012 IEEE.

关键词： Reinforcement learning

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Vibrational Feedback for a Teleoperated Continuum Robot with Non-contact Endoscope Localization

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Current Directions in Biomedical Engineering 2024年第1期10卷 17-20页

作者： Fischer, Jonas Andreas, Daniel Beckerle, Philipp Mathis-Ullrich, Franziska Marzi, Christian Friedrich-Alexander-University of Erlangen-Nuremberg Autonomous Systems and Mechatronics Paul-Gordan-Strase 3/5 Erlangen91052 Germany Friedrich-Alexander-University of Erlangen-Nuremberg Autonomous Systems and Mechatronics Erlangen91052 Germany Friedrich-Alexander-University of Erlangen-Nuremberg Surgical Planning and Robotic Cognition Lab Erlangen91052 Germany Karlsruhe Institute of Technology Institute for Anthropomatics and Robotics - Intelligent Process Automation & Robotics Karlsruhe76131 Germany

Limited or absent haptic feedback is reported as a factor hindering the continued adoption of surgical robots. This article presents a proof of concept for vibrotactile feedback integrated into a continuum robot to explore whether such feedback improves spatial perception in surgical settings. The robot is equipped with a capacitive sensor for noncontact endoscope localization, enabling spatial awareness of the robot's tool center point (TCP) within the surgical environment. The data from the sensor is processed and transmitted to a bracelet worn by the user, which generates vibrotactile feedback. The bracelet contains four vibration motors providing tactile cues for navigation and positioning of the robot's TCP. All subsystems are integrated into a unified system to deliver vibrotactile feedback to the user. When the user maneuvers the TCP of the robot near an object, they receive vibrotactile feedback via the bracelet. Thereby, the intensity of vibration increases as the TCP approaches the object, and the direction of the obstacle is mapped on the bracelet. Initial functional tests were performed and prove the functionality of the proposed system. © 2024 by Walter de Gruyter Berlin/Boston.

关键词： Capacitive sensors

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PRO-based Trajectory Planning for Spacecraft Close-Distance Flight around a Client Satellite for Proximity Operations

PRO-based Trajectory Planning for Spacecraft Close-Distance ...

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Accelerating Space Commerce, Exploration, and New Discovery Conference, ASCEND 2023

作者： Roach, Dylan Barth, Andrew Ma, Ou Fleming, Alex Hernandez, Michael Intelligent Robotics and Autonomous Systems Lab University of Cincinnati CincinnatiOH45221 United States iMetalX Group LLC SausalitoCA94965 United States

ISBN: (数字)9781624107054

ISBN: (纸本)9781624107054

In-space or On-orbit Servicing, Assembly, and Manufacturing (ISAM or OSAM) activities require spacecraft to fly around a client satellite or another orbiting object in a proximity range from 10’s to 0 meters in distance. When flying within such a close distance, it becomes extremely important for the servicing craft to fly safely avoiding collision but at the same time minimizing fuel consumption, especially since such fly-around spacecraft may likely be low-cost and less-capable CubeSats in future missions. Therefore, planning of a flight trajectory (i.e., relative-motion orbit) becomes essential for safe and reliable operations. So far, most of the research efforts have been focused on planning trajectories for rendezvous to a client satellite from 100’s of km away, but much less work has been done regarding flying around a client with a minimal but nonzero distance. However, for many ISAM tasks, such as to survey or inspect a client satellite at very close distance, one needs to plan one or more trajectories fully around the client body due to various requirements. These requirements may include specific image resolution, safety distance, an interesting spot, or full coverage of the entire client body, etc. Therefore, planning a safe and fuel-efficient circumnavigation trajectory becomes necessary. This paper first studied the characteristics of Passive Relative Orbits (PROs) around a client and proposed how to use these characteristics to plan a desirable task trajectory around the client. Then it solved the problem of how to deploy a spacecraft to a task trajectory along a two-burn PRO-based transfer trajectory and return from the task trajectory with minimal fuel consumption with or without a time constraint. Simulation examples are presented to quantitatively demonstrate the results of the presented trajectory planning methods for a client in typical LEO and GEO regions. © 2023, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved

关键词： Image resolution

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Convergence Analysis for Delay Dependent LFC Scheme for Power Systems Networks Over Open Communication Networks with Disturbances

Convergence Analysis for Delay Dependent LFC Scheme for Powe...

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2023 IEEE International Conference on Industrial Technology, ICIT 2023

作者： Islam, Shafiqul Ncf 263 Xavier University of Louisiana Dual-Degree Computer Science and Engineering Intelligent Robotics Mechatronics and Autonomous Systems Lab New OrleansLA70125 United States

ISBN: (纸本)9798350336504

This paper presents a delay-dependent convergence criterion for load frequency control (LFC) for smart power grid networks with the presence of disturbances and time-varying delays. The LFC scheme comprises delayed remote measurement and control signals with local state feedback signals. The convergence criteria are developed by using Lyapunov-Krasovskii functional for both symmetrical and asymmetrical time-varying delays associated with remote measurement and control channel. First, the analysis shows that all the power system states are bounded and asymptotically stable without the presence of disturbances. Then, the convergence analysis proves that all the power systems states are bounded and their bounds guarantee the convergence property of the H∞ control with the presence of bounded disturbances. These convergence properties are achieved by using well know Linear Matrix Inequalities (LMIs). Compared with the existing design, the proposed analysis uses both symmetrical and asymmetrical time-varying delays in the measurement channel from RTU to the control center and in the control channel from the control center to the power generation unit. In contrast with reported designs, the proposed design and analysis uses the disturbances associated with the closed loop systems appearing from modeling errors and other external load disturbances and faults. © 2023 IEEE.

关键词： Closed loop systems

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Integrating Task and Motion Planning for Manufacturing Processes 10

Integrating Task and Motion Planning for Manufacturing Proce...

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10th Italian Workshop on Artificial Intelligence and robotics, AIRO 2023

作者： Gottardi, Alberto Castaman, Nicola Pagello, Enrico Menegatti, Emanuele IT+Robotics srl Vicenza36100 Italy Intelligent Autonomous System Lab Dept. of Information Engineering University of Padova Padua35131 Italy Professional Industrial Consultant Bassano del Grappa36061 Italy

The synergy between the robot's abilities and human expertise provides several advantages in the industrial processes. A proper integration of Task and Motion Planning (TAMP), considering the interaction of the user with the environment is essential to maximize the benefits of robot-assisted tasks and to ensure safety in collaborative H-R tasks. However, the state of the art of the TAMP research field should be improved to overcome the limitations of the traditional TAMP approaches to be used in industrial scenarios. We illustrate a list of challenges to be solved in order to improve to manage efficiently the dynamism and uncertainty given by introducing a human operator into a robotized process of draping fiber carbon plies, with reference to the granted European Project DrapeBot. Finally, the proposed TAMP architecture is presented to address the challenges described. © 2024 Copyright for this paper by its authors.

关键词： Motion planning

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Image Data Augmentation through Generative Adversarial Networks for Waste Sorting

Image Data Augmentation through Generative Adversarial Netwo...

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IEEE International Conference on Simulation, Modeling, and Programming for autonomous Robots (SIMPAR)

作者： Alberto Bacchin Fabio Marangoni Alberto Gottardi Emanuele Menegatti Department of Information Engineering Intelligent Autonomous System Lab University of Padova Padua Italy IT+Robotics srl Vicenza Italy

ISBN: (数字)9798331516857

ISBN: (纸本)9798331516864

关键词： Waste materials Semantic segmentation Semantics Diversity reception Generative adversarial networks Data augmentation Generators Data models Sorting Synthetic data

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HortiBot: An Adaptive Multi-Arm System for Robotic Horticulture of Sweet Peppers

HortiBot: An Adaptive Multi-Arm System for Robotic Horticult...

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IEEE/RSJ International Conference on intelligent Robots and Systems (IROS)

作者： Christian Lenz Rohit Menon Michael Schreiber Melvin Paul Jacob Sven Behnke Maren Bennewitz Autonomous Intelligent Systems Lab University of Bonn Germany Center for Robotics Bonn Germany Humanoid Robots Lab University of Bonn Germany The Lamarr Institute Bonn Germany

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Horticultural tasks such as pruning and selective harvesting are labor intensive and horticultural staff are hard to find. Automating these tasks is challenging due to the semi-structured greenhouse workspaces, changing environmental conditions such as lighting, dense plant growth with many occlusions, and the need for gentle manipulation of non-rigid plant organs. In this work, we present the three-armed system HortiBot, with two arms for manipulation and a third arm as an articulated head for active perception using stereo cameras. Its perception system detects not only peppers, but also peduncles and stems in real time, and performs online data association to build a world model of pepper plants. Collision-aware online trajectory generation allows all three arms to safely track their respective targets for observation, grasping, and cutting. We integrated perception and manipulation to perform selective harvesting of peppers and evaluated the system in lab experiments. Using active perception coupled with end-effector force torque sensing for compliant manipulation, HortiBot achieves high success rates in our indoor pepper plant mock-up.

关键词： Torque Target tracking Horticulture Active perception Lighting Robot sensing systems Real-time systems Trajectory Sensors intelligent robots

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HortiBot: An Adaptive Multi-Arm System for Robotic Horticulture of Sweet Peppers

arXiv

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arXiv 2024年

作者： Lenz, Christian Menon, Rohit Schreiber, Michael Jacob, Melvin Paul Behnke, Sven Bennewitz, Maren Autonomous Intelligent Systems Lab University of Bonn Germany Humanoid Robots Lab University of Bonn Germany Center for Robotics Bonn Germany The Lamarr Institute Bonn Germany

关键词： End effectors

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PACC: A Passive-Arm Approach for High-Payload Collaborative Carrying with Quadruped Robots Using Model Predictive Control

PACC: A Passive-Arm Approach for High-Payload Collaborative ...

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IEEE/RSJ International Conference on intelligent Robots and Systems (IROS)

作者： Giulio Turrisi Lucas Schulze Vivian S. Medeiros Claudio Semini Victor Barasuol Dynamic Legged Systems Lab Istituto Italiano di Tecnologia (IIT) Intelligent Autonomous Systems Lab TU Darmstadt Legged Robotics Group Sao Paulo University (USP)

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In this paper, we introduce the concept of using passive arm structures with intrinsic impedance for robot-robot and human-robot collaborative carrying with quadruped robots. The concept is meant for a leader-follower task and takes a minimalist approach that focuses on exploiting the robots’ payload capabilities and reducing energy consumption, without compromising the robot locomotion capabilities. We introduce a preliminary arm mechanical design and describe how to use its joint displacements to guide the robot’s motion. To control the robot’s locomotion, we propose a decentralized Model Predictive Controller that incorporates an approximation of the arm dynamics and the estimation of the external forces from the collaborative carrying. We validate the overall system experimentally by performing both robot-robot and human-robot collaborative carrying on a stair-like obstacle and on rough terrain.

关键词： Collaboration Predictive models Manipulators Stability analysis Robustness Quadrupedal robots Impedance Collision avoidance Robots Payloads

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