Goal Recognition Control under Network Interdiction Using a Privacy Information Metric by Junren Luo, Xiang Ji, Wei Gao, Wanpeng Zhang, Shaofei Chen

“…After dual reformulating, the InfoGRC and InfoGRCT as bi-level mixed-integer programming problems, one Benders decomposition-based approach is adopted to optimize the observer’s optimal interdiction resource allocation and the actor’s cost-optimal path-planning. Finally, some experimental evaluations are conducted to demonstrate the effectiveness of the InfoGRC and InfoGRCT models in the task of controlling the goal recognition process.…”
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Hardware-Efficient Scheme for Trailer Robot Parking by Truck Robot in an Indoor Environment with Rendezvous by Divya Vani G, Srinivasa Rao Karumuri, Chinnaiah M C, Siew-Kei Lam, Janardhan Narambhatlu, Sanjay Dubey

“…The truck robot leads, and the trailer robot mimics the actions in the execution of path planning and parking. The truck robot was integrated with FPGA (Xilinx Zynq XC7Z020-CLG484-1), and the trailer was integrated with Arduino UNO computing devices; this heterogenous modeling is adequate in the execution of trailer parking by a truck. …”
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IN-ME Position Error Compensation Algorithm for the Near-Field Beamforming of UAVs by Yinan Zhang, Guangxue Wang, Yi Leng, Guowen Yu, Shirui Peng

“…In order to assess the mismatch of the phase error compensation function based on the proposed method, when the beam is scanning, the effectively compensated spatial area of the array beamforming is divided, which lays a foundation for subsequent spatial region division and unmanned aerial vehicle swarm path planning. The simulation results show that the beam formed by the method proposed in this paper has a lower sidelobe level, and as the signal-to-noise ratio changes, the robustness of the proposed method is better validated. …”
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Real‐time traffic cone detection for autonomous driving based on YOLOv4 by Qinghua Su, Haodong Wang, Min Xie, Yue Song, Shaobo Ma, Boxiong Li, Ying Yang, Liyong Wang

“…Via the YOLOv4 algorithm based on the Darknet platform and a detection result matching algorithm, the position of the traffic cone can be obtained and path planning can be performed. The results of experiments show that the proposed method can recognize red, blue, and yellow traffic cones in colour images with an average detection time of 35.46 ms and respective accuracies of 97.51%, 98.63%, and 97.29%. …”
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Task Space Trajectory Planning for Robot Manipulators to Follow 3-D Curved Contours by Juhyun Kim, Maolin Jin, Sang Hyun Park, Seong Youb Chung, Myun Joong Hwang

“…In the motion planning of a manipulator, path planning is carried out to determine a series of the positions of robot end effectors without collision. …”
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RockSeg: A Novel Semantic Segmentation Network Based on a Hybrid Framework Combining a Convolutional Neural Network and Transformer for Deep Space Rock Images by Lili Fan, Jiabin Yuan, Xuewei Niu, Keke Zha, Weiqi Ma

“…Rock detection on the surface of celestial bodies is critical in the deep space environment for obstacle avoidance and path planning of space probes. However, in the remote and complex deep environment, rocks have the characteristics of irregular shape, being similar to the background, sparse pixel characteristics, and being easy for light and dust to affect. …”
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Visual image design of the internet of things based on AI intelligence by Tian Tian

“…These include coordination in communication via IoT, sustainability of IoT network, and optimization challenges in path planning. Because of their limited battery life, these gadgets are limited in their range of communication. …”
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Trust in adaptive automation in a tactical search and navigation task by Broll, Anthony W

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Optimal Planning and Sampling Predictions for Autonomous and Lagrangian Platforms and Sensors in the Northern Arabian Sea by Shcherbina, Andrey, Lee, Craig, Gangopadhyay, Avijit, Lermusiaux, Pierre, Haley, Patrick, Jana, Sudip, Gupta, Abhinav, Kulkarni, Chinmay Sameer, Mirabito, Chris, Ali, Wael, Narayanan Subramani, Deepak, Dutt, Arkopal, Lin, Jing

“…This article reviews concepts and recent progress toward this principled approach, focusing on reachability, path planning, and adaptive sampling, and presents results of a real-time forecasting and planning experiment completed during February–April 2017 for the Northern Arabian Sea Circulation-autonomous research program. …”
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An incremental sampling-based algorithm for stochastic optimal control by Huynh, Vu Anh, Karaman, Sertac, Frazzoli, Emilio

“…Using the Markov chain approximation method and recent advances in sampling-based algorithms for deterministic path planning, we propose a novel algorithm called the incremental Markov Decision Process to incrementally compute control policies that approximate arbitrarily well an optimal policy in terms of the expected cost. …”
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Efficient planning for near-optimal contact-rich control under uncertainty by Guan, Charlie Zeyu

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Quantifying human decision-making: implications for bidirectional communication in human-robot teams by Roy, Nicholas

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Controlling a team of robots with a single input by Ayanian, Nora, Spielberg, Andrew, Arbesfeld, Matthew, Strauss, Jason, Rus, Daniela L

“…This approach allows the human user to solve the cognitive tasks such as path planning, while leaving precise motion to the robots. …”
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Robust multi-UAV planning in dynamic and uncertain environments by Tin, Chung, 1980-

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Nonlinear trajectory optimization with path constraints applied to spacecraft reconfiguration maneuvers by García, Ian Miguel

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Robust trajectory planning for unmanned aerial vehicles in uncertain environments by Luders, Brandon (Brandon Douglas)

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Bounding on Rough Terrain with the LittleDog Robot by Shkolnik, Alexander C., Levashov, Michael, Manchester, Ian R., Tedrake, Russell Louis

“…Rapidly Exploring Random Trees (RRTs) are known for fast kinematic path planning in high-dimensional configuration spaces in the presence of obstacles, but search efficiency degrades rapidly with the addition of challenging dynamics. …”
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Communication protocols for underwater data collection using a robotic sensor network by Singh, Hanumant, Hover, Franz S., Murphy, Christopher, Hollinger, Geoffrey A., Choudhary, Sunav, Qarabaqi, Parastoo, Mitra, Urbashi, Sukhatm, Gaurav S., Stojanovic, Milica

“…These simulations demonstrate that properly designed scheduling protocols are essential for choosing the appropriate path planning algorithms for data collection.…”
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Probabilistic Feasibility for Nonlinear Systems with Non-Gaussian Uncertainty using RRT by Luders, Brandon Douglas, How, Jonathan P.

“…However, the results in that paper require the dual assumptions of a linear system and Gaussian uncertainty, two assumptions which are often not applicable to many real-life path planning scenarios. This paper presents several extensions to the CC-RRT framework which allow these assumptions to be relaxed. …”
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Probabilistically safe motion planning to avoid dynamic obstacles with uncertain motion patterns by Aoude, Georges, Roy, Nicholas, How, Jonathan P., Luders, Brandon Douglas, Joseph, Joshua Mason

“…This paper presents a real-time path planning algorithm that guarantees probabilistic feasibility for autonomous robots with uncertain dynamics operating amidst one or more dynamic obstacles with uncertain motion patterns. …”
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