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Anticipating human motion is a key skill for intelligent systems that share a space or interact with humans

Accurate long-term predictions of human movement trajectories, body poses, actions or activities may significantly improve the ability of robots to plan ahead, anticipate the effects of their actions or to foresee hazardous situations. The topic has received increasing attention in recent years across several scientific communities with a growing spectrum of applications in service robots, self-driving cars, collaborative manipulators or tracking and surveillance.

This workshop is third in a series of ICRA 2019-2020 events. The aim of this workshop is to bring together researchers and practitioners from different communities and to discuss recent developments in this field, promising approaches, their limitations, benchmarking techniques and open challenges.

Workshop topics

Motion trajectory prediction in 2D and 3D
Predicting articulated human motion
Early action and activity recognition
Motion and task planning in dynamic environments considering motion predictions
Anticipation of group and crowd motion
Human motion prediction and safety
Human-robot Interaction considering predictions
Evaluation of prediction algorithms: datasets, metrics and benchmarks
Predictive planning and control
Applications of motion prediction techniques
Visual scene prediction

Workshop details

Participation

Participation in this workshop is free of charge and no registration is required. To connect, please follow this link: https://epfl.zoom.us/j/66418269303.

Recordings of all talks from 2021 and 2020 are available on the LHMP YouTube channel.

Program

The program of this workshop includes 8 talks, spotlight presentations for the selected papers and a trajectory prediction challenge. The full program can be accessed here, an outline is presented below.

In order to account for the diverse time zones of the invited speakers, the workshop will be split into the morning and the evening session in the Central European Summer Time zone (CEST). The talks will be recorded and all materials will be available on this website.

First session

Time CEST (PST)	Speaker	Topic
09:30 - 09:45 (00:30 - 00:45 AM)	Organizers	Welcome and Introduction
09:45 - 10:15 (00:45 - 01:15 AM)	Sami Haddadin, TUM	Safe Motion and Interaction in physical Human-Robot Interaction
10:15 - 10:45 (01:15 - 01:45 AM)	Dana Kulic, Monash University	Human motion prediction from demonstrations and interaction
10:45 - 11:00 (01:45 - 02:00 AM)	Break
11:00 - 11:30 (02:00 - 02:30 AM)	Lihui Wang, KTH	Motion Prediction for Human-Robot Collaborative Assembly
11:30 - 12:00 (02:30 - 03:00 AM)	TrajNet++ trajectory prediction challenge
12:00 - 12:10 (03:00 - 03:10 AM)	Organizers	Concluding the first session

Second session

Time CEST (PST)	Speaker	Topic
17:00 - 17:10 (08:00 - 08:10 AM)	Organizers	Introducing the second session
17:10 - 17:40 (08:10 - 08:40 AM)	Maren Bennewitz, University of Bonn	Anticipating Human Movements and Foresighted Robot Navigation Using Learned Human-Object Interactions
17:40 - 18:10 (08:40 - 09:10 AM)	Jonathan P. How, MIT	Context-aware learning of human motion prediction for safe autonomous driving
18:10 - 18:20 (09:10 - 09:20 AM)	Break
18:20 - 18:50 (09:20 - 09:50 AM)	Elena Corina Grigore, Motional	Motion Forecasting for Autonomous Driving Applications
18:50 - 19:20 (09:50 - 10:20 AM)	Benjamin Sapp, Waymo	Long term prediction in complex interactive environments
19:20 - 19:30 (10:20 - 10:30 AM)	Break
19:30 - 20:00 (10:30 - 11:00 AM)	Nick Rhinehart, UC Berkeley	Towards Learning to Forecast Everything for Making Complex Decisions
20:00 - 20:40 (11:00 - 11:40 AM)	Paper spotlight presentations
20:40 - 20:50 (11:40 - 11:50 AM)	Organizers	Concluding the second session