Plan Optimal Collision-Free Trajectories With Nonconvex Cost Functions Using Graphs of Convex Sets

The recently developed approach to motion planning in graphs of convex sets (GCS) provides an efficient framework for computing shortest-distance collision-free paths using convex optimization. This new motion planner is notably more computationally efficient than popular sampling-based motion planners, but it does not support nonconvex cost functions. This article develops a novel motion planning algorithm,…

Computationally Efficient Bayesian Model Predictive Control for 4-D Flight Trajectory Tracking Under Windy Conditions

Accurate 4-D trajectory tracking can improve trajectory predictability and further enhance the efficiency of air traffic management (ATM). However, the tracking accuracy is inevitably affected by uncertainties arising from wind. To maintain tracking performance, a novel Bayesian model predictive control (MPC) framework is proposed, within which a Bayesian recurrent neural network-based probabilistic wind prediction module…

Deep Visual Odometry for Stereo Event Cameras

Event-based cameras are bio-inspired sensors with pixels that independently and asynchronously respond to brightness changes at microsecond resolution, offering the potential to handle state estimation tasks involving motion blur and high dynamic range (HDR) illumination conditions. However, the versatility of event-based visual odometry (VO) relying on handcrafted data association (either direct or indirect methods) is…

Reinforcement Learning-Based Optimal Formation Control for Multiple WMRs With Visual Servoing

In this paper, a reinforcement learning (RL) control method is developed for the formation control of multiple wheeled mobile robots (WMRs) with visual servoing. First, a multi-robot system model is constructed based on the kinematic models of mobile robots, the camera model, and the multiple-view geometry principles. The leader-follower structure is then applied to derive…

SWIFT: A Distributed One-Stage Planner for Efficient Multi-Quadrotor Trajectory Optimization

This paper presents SWIFT (Swarm-Wise Inference for Fast Trajectory Planning), a distributed one-stage planner designed for efficient multi-quadrotor trajectory optimization in cluttered environments. SWIFT unifies depth-based perception, interaction-aware modeling, and trajectory prediction into a single lightweight network, enabling decentralized real-time planning without reliance on global maps. Each quadrotor processes its local depth observation and asynchronously…

Large Behavior Models Are Helping Atlas Get to Work

Boston Dynamics can be forgiven, I think, for the relative lack of acrobatic prowess displayed by the new version of Atlas in (most of) its latest videos. In fact, if you look at this Atlas video from late last year and compare it to Atlas’s most recent video, it’s doing what looks to be more…

Video Friday: Spot’s Got Talent

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.CLAWAR 2025: 5–7 September 2025, SHENZHEN, CHINAACTUATE 2025: 23–24 September 2025, SAN FRANCISCOCoRL 2025: 27–30 September…

A High-Payload Robotic Hopper Powered by Bidirectional Thrusters

Mobile robots have revolutionized various fields, offering solutions for manipulation, environmental monitoring, and exploration. However, payload capacity remains a limitation. This article presents a novel thrust-based robotic hopper capable of carrying payloads up to nine times its own weight while maintaining agile mobility over less structured terrain. The 220 g robot carries upto 2 kg…

SA-TP$^{2}$: A Safety-Aware Trajectory Prediction and Planning Model for Autonomous Driving

Trajectory prediction and planning remain key challenges for autonomous vehicles, particularly in complex and dynamic environments. Existing methods, typically based on static safety metrics like time-to-collision, fail to account for the evolving nature of risk in real-world traffic. This article proposes a novel safety-aware trajectory prediction and planning (SA-TP$^{2}$) model, which introduces an adaptive driver…