Robotics & Autonomy

37 verified cases, highest-rated first.

Industries: robotics 7, surgical robotics 4, agriculture 2, autonomous driving 2, autonomous vehicles 2, mobile robotics 2, industrial robotics / manufacturing 1, logistics robotics 1, drone delivery logistics 1, embodied AI 1, disaster relief logistics 1, assistive robotics 1

• Autonomous robotic laparoscopic surgery for intestinal anastomosis

  Autonomous laparoscopic soft-tissue surgery (intestinal anastomosis) is extremely difficult because it requires imaging, tissue tracking, surgical planning and precise control in deformable environments under motion and vision constraints.

  Robotics & Autonomy · 2022 · partially solved · 7/10 importance

• Precise and dexterous robotic manipulation via human-in-the-loop reinforcement learning

  Robots struggle with precise, dexterous real-world manipulation (assembly, dynamic handling, dual-arm coordination) needed for reliable industrial deployment.

  Robotics & Autonomy · 2025 · partially solved · 6/10 importance

• Learning robust autonomous navigation and locomotion for wheeled-legged robots

  Wheeled-legged robots need adaptive locomotion over varied terrains and efficient navigation around complex dynamic obstacles in urban environments.

  Robotics & Autonomy · 2024 · ai assisted · 6/10 importance

• Targeted weed management of Palmer amaranth using robotics and deep learning (YOLOv7)

  Traditional herbicide spraying is indiscriminate, harming the environment and crops; Palmer amaranth is Nebraska's most troublesome weed.

  Robotics & Autonomy · 2024 · partially solved · 6/10 importance

• Deep reinforcement learning navigation via decision transformer in autonomous driving

  Improving navigation decision-making for autonomous vehicles in partially observable urban environments with sensor noise and occlusion.

  Robotics & Autonomy · 2024 · ai assisted · 6/10 importance

• Genetic-Algorithm-Aided Deep Reinforcement Learning for Multi-Agent Drone Delivery

  Planning efficient multi-agent drone delivery is hard because the planning space grows exponentially with the number of agents.

  Robotics & Autonomy · 2024 · ai assisted · 6/10 importance

• PaLM-E: An Embodied Multimodal Language Model

  Large language models lack grounding in the real world: linking words to continuous sensor percepts is a challenge for robotics and real-world inference.

  Robotics & Autonomy · 2023 · partially solved · 6/10 importance

• Formation of a Lightweight, Deep Learning-Based Weed Detection System for a Commercial Autonomous Laser Weeding Robot

  Weeds cause major crop yield losses (over PKR 65 billion per year in Pakistan), and autonomous laser weeding robots need accurate real-time weed detection to avoid damaging crops.

  Robotics & Autonomy · 2023 · ai assisted · 6/10 importance

• A Hybrid Deep Reinforcement Learning and Optimal Control Architecture for Autonomous Highway Driving

  Autonomous vehicles must choose optimal driving decisions in highly variable and unpredictable highway traffic scenarios, which is a challenging planning task.

  Robotics & Autonomy · 2023 · ai assisted · 6/10 importance

• A Drone Scheduling Method for Emergency Power Material Transportation Based on Deep Reinforcement Learning Optimized PSO Algorithm

  Existing drone flight trajectory optimization models cannot meet the needs of emergency power material distribution in mountainous areas after disasters.

  Robotics & Autonomy · 2023 · ai assisted · 6/10 importance

• Towards Deep Radar Perception for Autonomous Driving: Datasets, Methods, and Challenges

  Deep learning for automotive radar perception is spread across tasks without a holistic overview, and challenges like multi-path effects, uncertainty, and adverse weather remain.

  Robotics & Autonomy · 2022 · ai assisted · 6/10 importance

• Assistive Navigation Using Deep Reinforcement Learning Guiding Robot With UWB/Voice Beacons and Semantic Feedbacks for Blind and Visually Impaired People

  People who are blind and visually impaired struggle to navigate pedestrian environments independently, and SLAM-based robots are vulnerable in dynamic settings.

  Robotics & Autonomy · 2021 · partially solved · 6/10 importance

• Solving Rubik's Cube with a Robot Hand

  Solving a Rubik's cube with a real humanoid robot hand requires robust control and state estimation despite the sim-to-real gap.

  Robotics & Autonomy · 2019 · solved · 6/10 importance

• Champion-level drone racing using deep reinforcement learning

  Autonomous drones could not match professional human pilots in high-speed first-person-view racing using only onboard sensing.

  Robotics & Autonomy · 2023 · solved · 5/10 importance

• Learning quadrupedal locomotion on deformable terrain

  Reinforcement learning control policies for legged robots fail on soft, deformable terrains, especially at high speed, because they cannot generalize beyond training data.

  Robotics & Autonomy · 2023 · ai assisted · 5/10 importance

• Deep Reinforcement Learning for Truck-Drone Delivery Problem

  Optimally scheduling mixed truck-drone delivery operations over real road networks despite drone range and payload limits.

  Robotics & Autonomy · 2023 · ai assisted · 5/10 importance

• Axis-space framework for cable-driven soft continuum robot control via reinforcement learning

  Deep reinforcement learning control of cable-driven soft continuum robots (used in minimally invasive surgery) suffers from high sample complexity and a simulation-to-real-world gap.

  Robotics & Autonomy · 2023 · partially solved · 5/10 importance

• Model-free reinforcement learning for robust locomotion using demonstrations from trajectory optimization

  Creating locomotion policies robust enough to deploy directly on real robots, where training from scratch on hardware is impractical.

  Robotics & Autonomy · 2022 · partially solved · 5/10 importance

• Deep reinforcement learning for real-world quadrupedal locomotion: a comprehensive review

  Building agile, intelligent controllers for four-legged (quadrupedal) robots, a long-standing challenge in robotics and AI.

  Robotics & Autonomy · 2022 · ai assisted · 5/10 importance

• Deep reinforcement learning for map-less goal-driven robot navigation

  Mobile robots normally need an explicit map of the environment to navigate, which is impractical or impossible in new or dynamic environments. The study developed a local navigation method that steers a robot to global goals without a map.

  Robotics & Autonomy · 2021 · partially solved · 5/10 importance

• Deep Reinforcement Learning for End-to-End Local Motion Planning of Autonomous Aerial Robots in Unknown Outdoor Environments: Real-Time Flight Experiments

  Micro aerial vehicles must autonomously navigate obstacles and reach goals in unknown, GPS-denied outdoor environments despite limited size and computational power.

  Robotics & Autonomy · 2021 · solved · 5/10 importance

• Object Manipulation with an Anthropomorphic Robotic Hand via Deep Reinforcement Learning with a Synergy Space of Natural Hand Poses

  Anthropomorphic robotic hands with many degrees of freedom are hard to control for human-like grasping and relocation of variously shaped objects.

  Robotics & Autonomy · 2021 · ai assisted · 5/10 importance

• Learning Mobile Manipulation through Deep Reinforcement Learning

  Whole-body mobile manipulation in unstructured environments using only on-board sensors is harder than fixed-base manipulation because the mobile base and manipulator must coordinate.

  Robotics & Autonomy · 2020 · ai assisted · 5/10 importance

• Motion2Vec: Semi-Supervised Representation Learning from Surgical Videos

  Learning to segment and understand surgical actions from video demonstrations is hard because labeled surgical video data is scarce.

  Robotics & Autonomy · 2020 · ai assisted · 5/10 importance

• Deep reinforcement learning for multi-agent coordination

  Multiple robots working in narrow, confined environments suffer congestion and interference that hinder collective task performance, and coordinating them without explicit communication is hard.

  Robotics & Autonomy · 2025 · partially solved · 4/10 importance

• A Review of Deep Learning Advancements in Road Analysis for Autonomous Driving

  Autonomous vehicles need reliable road damage detection and road surface classification for safe driving, and the field lacks a clear comparison of deep learning methods.

  Robotics & Autonomy · 2024 · ai assisted · 4/10 importance

• Autonomous Underwater Vehicle Docking Under Realistic Assumptions Using Deep Reinforcement Learning

  Autonomously homing and docking an underwater vehicle under realistic, noisy ocean conditions where traditional controllers struggle.

  Robotics & Autonomy · 2024 · partially solved · 4/10 importance

• HAVEN: Hierarchical Cooperative Multi-Agent Reinforcement Learning with Dual Coordination Mechanism

  Instability arises when policies of multiple levels and agents are optimized concurrently in fully cooperative multi-agent tasks.

  Robotics & Autonomy · 2023 · ai assisted · 4/10 importance

• Bridging Locomotion and Manipulation Using Reconfigurable Robotic Limbs via Reinforcement Learning

  Robots usually learn locomotion and manipulation separately; unifying both skills on reconfigurable limbs lacked data-driven evidence.

  Robotics & Autonomy · 2023 · ai assisted · 4/10 importance

• Continuous control actions learning and adaptation for robotic manipulation through reinforcement learning

  Programming robots to perform continuous-control object manipulation tasks and adapt them to changed environments is difficult and slow.

  Robotics & Autonomy · 2022 · solved · 4/10 importance

• Weld Seam Identification and Tracking of Inspection Robot Based on Deep Learning Network

  Autonomous inspection robots on large spherical tanks need to accurately identify and track weld seams to inspect them regularly, which remained a challenge.

  Robotics & Autonomy · 2022 · solved · 4/10 importance

• Obstacle Avoidance Drone by Deep Reinforcement Learning and Its Racing with Human Pilot

  Training drones to avoid obstacles without the laborious labeled datasets that supervised learning requires.

  Robotics & Autonomy · 2019 · ai assisted · 4/10 importance

• Automated robot‐assisted surgical skill evaluation: Predictive analytics approach

  Surgical skill assessment has predominantly been subjective, lacking objective automated evaluation of surgeon performance.

  Robotics & Autonomy · 2017 · partially solved · 4/10 importance

• Machine learning–driven self-discovery of the robot body morphology

  Robot morphology is typically assumed known and calibrated via external measuring devices; whether a robot can learn elements of its own body morphology by itself was largely unexplored.

  Robotics & Autonomy · 2023 · partially solved · 3/10 importance

• Scaling multi-agent reinforcement learning to full 11 versus 11 simulated robotic football

  Simulated RoboCup football teams still rely on handcrafted strategies, and reinforcement learning had not been scaled to the full 22-player game.

  Robotics & Autonomy · 2023 · partially solved · 3/10 importance

• Dexterous robotic manipulation using deep reinforcement learning and knowledge transfer for complex sparse reward‐based tasks

  Getting a TriFinger robot to dexterously manipulate a cube along a specified positional trajectory under sparse rewards, where traditional control methods struggled.

  Robotics & Autonomy · 2022 · solved · 3/10 importance

• The Structure, Design, and Closed-Loop Motion Control of a Differential Drive Soft Robot

  Steering an inchworm-inspired pneumatic soft robot is difficult because its motion is nonlinear, making closed-loop automatic control hard to achieve.

  Robotics & Autonomy · 2017 · ai assisted · 3/10 importance

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