This paper improves safe motion primitives-based teleoperation of a multirotor by developing a hierarchical collision avoidance method that modulates maximum speed based on environment complexity and perceptual constraints. Safe speed modulation is challenging in environments that exhibit varying clutter. Existing methods fix maximum speed and map resolution, which prevents vehicles from accessing tight spaces and places the cognitive load for changing speed on the operator. We address these gaps by proposing a high-rate (10 Hz) teleoperation approach that modulates the maximum vehicle speed through hierarchical collision checking. The hierarchical collision checker simultaneously adapts the local map's voxel size and maximum vehicle speed to ensure motion planning safety. The proposed methodology is evaluated in simulation and real-world experiments and compared to a non-adaptive motion primitives-based teleoperation approach. The results demonstrate the advantages of the proposed teleoperation approach both in time taken and the ability to complete the task without requiring the user to specify a maximum vehicle speed.
Predictive Relative-Velocity Steering for Safe Robotic Manipulator Teleoperation in Dynamic Environments
Zhejiang University（浙江大学）；University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；Tsinghua University（清华大学）；Institute for Embodied Intelligence and Robotics, Tsinghua University（清华大学具身智能与机器人研究所）；TetraBOT
Effective Virtual Reality Teleoperation of an Upper-body Humanoid with Modified Task Jacobians and Relaxed Barrier Functions for Self-Collision Avoidance
Collision Avoidance in Pedestrian-Rich Environments with Deep Reinforcement Learning
National Institute of Standards and Technology（美国国家标准与技术研究院）；Colorado State University（科罗拉多州立大学）；University of Colorado（科罗拉多大学）；Massachusetts Institute of Technology（麻省理工学院）；Facebook Reality Labs（Facebook现实实验室）
Safety-Critical Whole-Body Control for Humanoid Robots via Input-to-State Safe Control Barrier Functions
Department of Intelligence and Information, Seoul National University（智能信息系，首尔国立大学）；Robotics Lab, Hyundai Motor Group（Hyundai Motor Group 机器人实验室）；Advanced Institute of Convergence Technology（融合技术高级研究院）
Local Path Planning and Obstacle Avoidance for an Omnicopter Platform
Faculty of Aerospace Engineering, Delft University of Technology（代尔夫特理工大学航空航天工程学院）；Mohamed Bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）；Center for Artificial Intelligence and Robotics, New York University Abu Dhabi（纽约大学阿布扎比分校人工智能与机器人中心）
Whole-body motion planning and safety-critical control for aerial manipulation
School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore（机械与航空航天工程学院，南洋理工大学，新加坡）；Department of Aerospace Engineering, Seoul National University, South Korea（航空航天工程系，首尔国立大学，韩国）
