Human–robot collaboration poses many challenges where humans and robots work inside a shared workspace. Robots collaborating with humans indirectly bring difficulties for accomplishing co-carrying tasks. In our work, we focus on co-carrying an object by robots in cooperation with humans using visual and force sensing. A framework using visual and force sensing is proposed for human–robot co-carrying tasks, enabling robots to actively cooperate with humans and reduce human efforts. Visual sensing for perceiving human motion is involved in admittance-based force control, and a hybrid controller combining visual servoing with force feedback is proposed which generates refined robot motion. The proposed framework is validated by a co-carrying task in experiments. There exist two phases in experimental processes: in Phase 1 , the human hand holds one side of the box object, and the robot gripper of the Baxter robot automatically approaches to the other side of the box object and finally holds it; in Phase 2 , the human and the Baxter robot co-carry the box object over a distance to different target positions. This article is part of the theme issue ‘Towards symbiotic autonomous systems’.

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This paper addresses the path planning and autonomous obstacle avoidance problem of UAVs in urban dynamic area. A flight path planning strategy for UAVs in complex urban environments is proposed.First, the A* algorithm is used to construct a desired global path in a 3D static environment, which is used as the static reference path for dynamic obstacle avoidance below.The environmental and the key points of algorithm are also elaborated. In this paper, the dynamic obstacles are divided into three categories, then, in order to avoid the collision between dynamic obstacles and static optimal paths, two strategies to achieve local online path adjustment are proposed. Finally, the seven order minimum snap trajectories generation based on piecewise polynomials is utilized to smooth the flight path.We can obtain a smooth trajectory based on UAV dynamics and safety. The simulation results verify the effectiveness of the proposed UAV path planning strategy in the dynamic and complex urban area.

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