This paper presents a novel control approach to dealing with object slip during robotic manipulative movements. Slip is a major cause of failure in many robotic grasping and manipulation tasks. Existing works increase grip force to avoid/control slip. However, this may not be feasible when (i) the robot cannot increase the gripping force -- the max gripping force is already applied or (ii) increased force damages the grasped object, such as soft fruit. Moreover, the robot fixes the gripping force when it forms a stable grasp on the surface of an object, and changing the gripping force during real-time manipulation may not be an effective control policy. We propose a novel control approach to slip avoidance including a learned action-conditioned slip predictor and a constrained optimiser avoiding a predicted slip given a desired robot action. We show the effectiveness of the proposed trajectory adaptation method with receding horizon controller with a series of real-robot test cases. Our experimental results show our proposed data-driven predictive controller can control slip for objects unseen in training.
Perception, Control and Hardware for In-Hand Slip-Aware Object Manipulation with Parallel Grippers
Department of Electrical Engineering, Chalmers University of Technology, Sweden（电气工程系，查尔姆斯理工大学，瑞典）；Department of Automatic Control, Lund University, Sweden（自动控制系，隆德大学，瑞典）
Two-layer adaptive trajectory tracking controller for quadruped robots on slippery terrains
Institute of Computer Science, Foundation for Research and Technology–Hellas（希腊基础研究与技术基金会计算机科学研究所）；Hellenic Mediterranean University（希腊地中海大学）；University of Crete（克里特大学）
Historical Prediction Attention Mechanism based Trajectory Forecasting for Proactive Work Zone Safety in a Digital Twin Environment
The University of Alabama（阿拉巴马大学）；MITRE Corporation（MITRE公司）；University of Nebraska-Lincoln（内布拉斯加大学林肯分校）；FAMU-FSU College of Engineering（佛罗里达大学-佛罗里达州立大学工程学院）
Nonlinear Stochastic Trajectory Optimization for Centroidal Momentum Motion Generation of Legged Robots
Max Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）；LAAS-CNRS（LAAS-法国国家科学研究中心）；Université de Toulouse（图卢兹大学）；CNRS（法国国家科学研究中心）；University of Trento（特伦托大学）；Tandon School of Engineering, New York University（纽约大学坦登工程学院）
Spatiotemporal Receding Horizon Control with Proactive Interaction Towards Autonomous Driving in Dense Traffic
The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；Great Bay University（大湾区大学）；The Hong Kong University of Science and Technology（香港科技大学）；HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute（香港科技大学深港协同创新研究院）
TacMan-Turbo: Proactive Tactile Control for Robust and Efficient Articulated Object Manipulation
Peking University（北京大学）；State Key Lab of General AI at Peking University（北京大学通用人工智能国家重点实验室）；PKU-BingJi Joint Laboratory for Artificial Intelligence（北京大学-百度智云人工智能联合实验室）；Wuhan Major Scientific and Technological Special Program（武汉重大科技专项）；Hubei Embodied Intelligence Foundation Model Research and Development Program（湖北省具身智能基础模型研发计划）；National Comprehensive Experimental Base for Governance of Intelligent Society（智能社会治理国家综合实验基地）；LeapZenith AI Research（LeapZenith人工智能研究）；Tsinghua University（清华大学）；Embodied Intelligence Lab（具身智能实验室）；PKU-Wuhan Institute for Artificial Intelligence（北京大学-武汉人工智能研究院）；University of Chinese Academy of Sciences（中国科学院大学）
Adap-RPF: Adaptive Trajectory Sampling for Robot Person Following in Dynamic Crowded Environments
Robotics and Computer Vision (RCV) Laboratory, Southern University of Science and Technology (SUSTech), Shenzhen, China（机器人与计算机视觉实验室，南方科技大学，深圳，中国）；SUSTech（南方科技大学）
Universal Trajectory Optimization Framework for Differential Drive Robot Class
The State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University（工业控制技术国家重点实验室，控制科学与工程学院，浙江大学）；Huzhou Institute, Zhejiang University（湖州研究院，浙江大学）；China Tobacco Zhejiang Industrial Co., Ltd.（中国烟草浙江工业公司）
PathFormer: A Transformer with 3D Grid Constraints for Digital Twin Robot-Arm Trajectory Generation
Department of Computer Science, University of Missouri–Kansas City (UMKC)（密苏里大学哥伦比亚分校计算机科学系）；Department of Computer Science, California State University, Fullerton（加州州立大学富尔顿分校计算机科学系）
Unified Linear Parametric Map Modeling and Perception-aware Trajectory Planning for Mobile Robotics
School of Information Science and Engineering, Shenyang University of Technology（沈阳理工大学信息科学与工程学院）；State Key Laboratory of Synthetic Automation for Process Industries, Northeastern University（东北大学过程工业综合自动化重点实验室）；State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences（中国科学院沈阳自动化研究所机器人重点实验室）；University of Chinese Academy of Sciences（中国科学院大学）
