Problem

Due to booming of e-commerce in combination with labor shortage, providers of logistics process automation are seeking for new robot technologies to maintain/expand capacity and reduce cycle time of take-and-put operations. 

Solution

I.AM. proposes to tackle the challenge of reducing the cycle time (and footprint) in take-and-put operations in logistics by exploiting dynamic manipulation, allowing for intentional robot-object-environment collisions

Approach

Europe is leading the market of torque-controlled robots. These robots can withstand physical interaction with the environment, while providing accurate sensing and actuation capabilities. I.AM. leverages and strengthens European leadership by endowing robots to exploit intentional impacts for manipulation. At the same time, it will explore the limits of commercially available robots in the context of impact-aware manipulation and will help in creating a roadmap for next impact-aware and impact-resilient robots.

Scenarios

I.AM. will target three validation scenarios (TOSS, BOX, GRAB), inspired by real industrial use cases.

TOSS

BOX

GRAB

I.AM. has received funding from the European Union's Horizon 2020 Research and Innovation Programme (call: H2020-ICT-09-2019-2020, RIA) under Grant Agreement No. 871899